SlideShare ist ein Scribd-Unternehmen logo
1 von 48
IBS Statistics Year 1
     Dr. Ning DING




                     n.ding@pl.hanze.nl
                     I007, Friday & Monday
Table of content
• Chapter 1: What is statistics?
   –   Why study statistics?
   –   What is meant by statistics?
   –   Types of statistics
   –   Types of variables
   –   Levels of measurement
        • Norminal-Level Data
        • Ordinal-Level Data
        • Interval-Level Data
   – Ethics and Statistics
• Chapter 2: Describing data
   – Frequency tables
   – Frequency distributions
   – Graphic presentation
Learning Goals
• Chapter 1: What is statistics?
   – Understand why we study statistics
   – Explain what is meant by descriptive and inferential statistics
   – Distinguish between a qualitative and quantitative variable
   – Describe how a discrete variable is different from a continous
     variable
   – Distinguish among the nominal, ordinal, interval and ratio
     levels of measurement
• Chapter 2: Describing data
   –   Organize qualitative data into a frequency table
   –   Present a frequency table as a bar chart or a pie chart
   –   Organize quantitative data into a freqency distribution
   –   Present a frequency distribution for quantitative data using
       histograms, frequency polygons, and cumulative frequency
       polygons.
Chapter 1: What is Statistics?


            1. Introduction


Statistics are
everywhere.
Chapter 1: What is Statistics?


1. Introduction
Chapter 1: What is Statistics?


             1. Introduction


Statistics
help you
make
decisions.
Chapter 1: What is Statistics?


           1. Introduction


Statistics give
you a better
understanding.
Chapter 1: What is Statistics?


                       1. Introduction

1. Adequate information? Additional information?


2. No misleading information?


3. Summarize the information.


4. Analyze available information.


5. Conclusions!
Chapter 1: What is Statistics?


              1. Introduction

Statistics:

The science of collecting, organizing,
presenting, analyzing and interpreting data
to assist in making more effective decisions.
Chapter 1: What is Statistics?


               1. Introduction
                Making decisions

                                Interpret data

                         Present data

                 Analyze data

        Organize data

Collect data
Chapter 1: What is Statistics?


        2. Types of Statistics

Descriptive Statistics:

Methods of organizing, summarizing and
presenting data in an informative way.


Inferential Statistics:

Methods used to estimate a property of a
population on the basis of a sample.
Chapter 1: What is Statistics?


              2. Types of Statistics

Descriptive                         Inferential
Statistics:                         Statistics:
Chapter 1: What is Statistics?


         2. Types of Statistics

Population:

The entire set of individual or objects of
interest or the measurements obtained from all
individuals or objects of interest.

Sample:

A portion, or part, of the population of interest.
Chapter 1: What is Statistics?


          2. Types of Statistics

Population:
Sample:




           Play
Chapter 1: What is Statistics?


        3. Types of Variables

Qualitative:

nonnumeric, attribute




Quantitative:

numerical
Chapter 1: What is Statistics?


3. Types of Variables
     Quantitative:




      Qualitative:
Chapter 1: What is Statistics?


         3. Types of Variables
Discrete counting   or   Continuous measuring
Chapter 1: What is Statistics?


    4. Levels of Measurement
Nominal:
  •Data categories are represented by labels or names.
  •Even when the labels are numerically coded, the data categories
  have no logical order.
      •Example:
          •Eye colour, gender, religious affiliation

Ordinal:
  •Data classifications are represented by sets of labels or names
  (high, medium, low) that have relative values.
  •Because of the relative values, the data classified can be ranked or
  ordered.
      •Example:
          •During a taste test of 4 soft drinks, Mellow Yellow was
          ranked number 1, Sprite number 2, Seven-up number 3, and
          Orange Crush number 4.
Chapter 1: What is Statistics?


      4. Levels of Measurement
 Nominal:                    Ordinal:




No logical order           Ranked or ordered
Chapter 1: What is Statistics?


     4. Levels of Measurement
Interval:
   •Similar to the ordinal level, with the additional property that
   meaningful amounts of differences between data values can be
   determined.
   •There is no natural zero point.
       •Example:
            •Temperature on the Fahrenheit scale.


Ratio:
   •The interval level with an inherent zero starting point.
   •Differences and ratios are meaningful for this level of measurement.
        •Examples:
            •Monthly income; distance travelled by manufacturer’s
            representatives per month.
Chapter 1: What is Statistics?


    4. Levels of Measurement
            Online Animation




Nominal:

Ordinal:

Interval:
                               Ordered, Equal differences

 Ratio:
                               Zero
vels of Measurement    Chapter 1: What is Statistics?


     4. Levels of Measurement
Chapter 1: What is Statistics?


                      Exercises 1-a


For each of the following, determine whether the group is a
sample or a population.

•The participants in a study of a new cholesterol drug.       Sample

•The drivers who received a speeding ticket Kansas City last month.
                                                                Population

•Those on welfare in Cook County (Chicago), Illinois.
                                                         Population
•The 30 stocks reported as a part of the Dow Jones Industrial
Average.                                                       Sample



                                                                      P14. N.4 Ch.1
Chapter 1: What is Statistics?


                    Exercises 1-b


Refer to the Real Estate data at the back of the text, which
report information on homes sold in the Denver, Colorado,
area last year. Consider the following variables: selling
price, number of bedrooms, township, and distance
from the center of the city.

•Which of the variables are qualitative and which are
quantitative?

   township      all the rest…

•Determin the level of measurement for each of the
variables.
  Township = nominal level        All the rest…=ratio
                                                                      P18. N.16 Ch.1
Chapter 2: Describing data


              2.1 Frequency Table
 Frequency Table:
     •A grouping of qualitative data into mutually exclusive classes
     showing the number of observations in each class.

Example: Ice cream 20 vendors
     Choco 6     7 5     7   7   8   7   6   9   7
     Vanilla 4   10 6    8   8   9   5   6   4   8
Chapter 2: Describing data


              2.1 Frequency Table
 Relative Class Frequencies:
     •Show the fraction of the total number of observations in each class
Example: Ice cream 20 vendors
        Choco 6     7 5    7    7   8   7   6   9    7
        Vanilla 4   10 6   8    8   9   5   6   4    8
Chapter 1: What is Statistics?


                           Exercises 2-a

A total of 1,000 residents in Minnesota were asked which season they preferred. The
results were 100 liked winter best, 300 liked spring, 400 liked summer, and 200 liked
fall.

If the data were summarized in a frequency table, how many classes would be
used? What would be the relative frequencies for each class?




                                                                        P27. N.3 .Ch.2
Chapter 2: Describing data
                   2.2 Graphic Presentation
                      of Qualitative Data
   Bar Chart:
       •The classes are reported on the horizontal axis
       •The class frequencies on the vertical axis
       •The class frequencies are proportional to the heights of the bars.
Example: Ice cream 20 vendors
                                   Ice Cream Sales

                  70   Choco, 69
                                                     Vanilla, 68


                  65


                                                                      Choco
           Axis




                  60
                                                                      Vanilla


                  55



                  50
                        Choco                         Vanilla
                                       Types
Chapter 2: Describing data
             2.2 Graphic Presentation
                of Qualitative Data
   Pie Chart:
       •Shows the proportion or percent that each class represents of the
       total number of frequencies


Example: Ice cream 20 vendors




          49.64%
                                    50.36%
                                                     1
                                                     2
Chapter 2: Describing data


              2. Frequency Distribution

Frequency Distribution:
  •A grouping of data into
  mutually exclusive
  classes showing the
  number of observations in
  each class.
Chapter 2: Describing data


       2. Frequency Distribution

Frequency Distribution:
  •A grouping of data into mutually exclusive classes showing the
  number of observations in each class.
Chapter 2: Describing data


                 2. Frequency Distribution
Step 1: Just enough recipe 2 to the k rule




     N=27 number of class=5
Step 2: Class Interval
                                              10 -< 20          4
                                              20 -< 30          1
                 (55-14)/5 ≈ 8                30 -< 40          10
Step 3: Choose nice “round” boundaries        40 -< 50          9
Step 4: Try to avoid empty and open classes
                                              50 -< 60          3

                                                               N=27
      Practice
Chapter 2: Describing data


                          Exercises 2-b

A set of data consists of 45 observations between $0 and $29. What size would you
recommend for the class interval?


           25 = 32, 26 = 64, suggests 6 classes


           i>        $30 - $0       =5
                       6

           Use interval of 5


                                                                     P33. N.8 .Ch.2
Chapter 2: Describing data


                             Exercises 2-b

The Quick Change Oil Company has a number of outlets in the metropolitan Seattle
area. The daily number of oil changes at the Oak Street outlet in the past 20 days
are:

              65       98   55   62 79   59 51 90 72       56
              70       62   66   80 94   79 63 73 71       85
 a. How many classes would you recommend?

  a.    24 = 16, 25 = 32, suggests 5 classes
 b. What class interval would you suggest?

            99 - 51
  i>                             ≈ 9     b. Use interval of 10
                   5                                                 P34. N.12.Ch.2
Chapter 2: Describing data


                           Exercises 2-b

The Quick Change Oil Company has a number of outlets in the metropolitan Seattle
area. The daily number of oil changes at the Oak Street outlet in the past 20 days
are:

              65   98   55   62 79     59 51 90 72         56
              70   62   66   80 94     79 63 73 71         85
c. What lower limit would you recommend for the first class?

           c. 50




                                                                     P34. N.12.Ch.2
Chapter 2: Describing data


             3. Graphic Presentation

Histogram
  •The classes are marked on the horizontal axis
  •The class frequencies on the vertical axis
  •The class frequencies are represented by the heights of the bars
  and the bars are adjacent to each other.




Polygon:
  •The shape of a distribution
  •Similar to a histogram
Chapter 2: Describing data


                                   3. Graphic Presentation
     Histogram

     Example:

                  16   Amount of € spent on books by 50 students
                  14

                  12
No. of students




                  10

                   8

                   6

                   4

                   2

                   0
                        25   75   125   175   225   275   325   375   425

                                          Amount in €
Chapter 2: Describing data


                                    3. Graphic Presentation
                  Polygon

                  Example:
                       Amount of € spent on books by 50 students
                  16

                  14

                  12
No. of students




                  10

                   8

                   6

                   4

                   2

                   0
                             125   175   225     275   325   375   425

                                         Amount in €
Chapter 2: Describing data


                                               3. Graphic Presentation

                             Cumulative frequency distribution:
                             used to determine how many or what proportion of
                             the data values are below or above a certain value.
                            Amount of € spent on books by 50
                                        students
                       60

                       50
Cumulative frequency




                       40

                       30

                       20

                       10

                        0
                             100   150   200    250   300    350   400   450

                                               Amount in €
Chapter 2: Describing data


3. Graphic Presentation
Chapter 1: What is Statistics?


                        Summary
• Chapter 1: What is statistics?
   – Understand why we study statistics
   – Explain what is meant by descriptive and inferential statistics
   – Distinguish between a qualitative and quantitative variable
   – Describe how a discrete variable is different from a continous
     variable
   – Distinguish among the nominal, ordinal, interval and ratio
     levels of measurement
• Chapter 2: Describing data
   –   Organize qualitative data into a frequency table
   –   Present a frequency table as a bar chart or a pie chart
   –   Organize quantitative data into a freqency distribution
   –   Present a frequency distribution for quantitative data using
       histograms, frequency polygons, and cumulative frequency
       polygons.
Chapter 1: What is Statistics?


                    Exercises 1-a


What is the level of measurement for each of the following
  variables?
• A. student IQ ratings Interval
• B. distance students travel to class Ratio
• C. student scores on the first statistics test Interval
• D. a classification of students by state of birth Nominal
• E. a ranking of students as freshmen, sophomore, junior, and
  senior Ordinal
• F. Number of hours students study per week Ratio
Chapter 1: What is Statistics?


                                   Exercises 1-b


       Place these variables in the following classification tables.
a.   Salary
b.   Gender                                 Discrete                                Continuous
c.   Sales
     volumen of
                                    b. Gender         d. Soft drink preference
     MP3 players    Qualitative
d.   Soft drink
     preference
e.   Temperature                   f. SAT scores
f.   SAT scores                                                         a. Salary
g.   Student rank
                                   g. Student rank in class             c. Sales volume of MP3 players
     in class       Quantitative
h.   Rating of a
                                   h. Rating of a finance professor     e. Temperature
     finance
     professor
                                                                        i. Number of home computers
i.   Number of
     home
     computers                                                                           P16. N.9 Ch.1
Chapter 1: What is Statistics?


                               Exercises 1-c


       Place these variables in the following classification tables.
a.   Salary
b.   Gender                             Discrete                              Continuous
c.   Sales
     volumen of
                               b. Gender
     MP3 players    Nominal
d.   Soft drink
     preference                d. Soft drink preference
e.   Temperature
                    Ordinal
f.   SAT scores                g. Student rank in class   h. Rating of a finance professor
g.   Student rank
     in class                  f. SAT scores                      e. Temperature
h.   Rating of a
                    Interval
     finance                                                      a. Salary
     professor
i.   Number of      Ratio                                         c. Sales volume of MP3 players
     home
     computers                                                    i. Number of home computers
Chapter 1: What is Statistics?


                    Exercises 1-d
                                The table below reports the number of
                                cars and light trucks sold by the Big
                                Three automobile manufacturers for
                                June 2004 and June 2005.




1. Compare the total sales in the two months. What do you conclude? Has
there been an increase in sales?




                                                               P17. N.13 Ch.1
Chapter 1: What is Statistics?


                    Exercises 1-d
                                The table below reports the number of
                                cars and light trucks sold by the Big
                                Three automobile manufacturers for
                                June 2004 and June 2005.




1. Compare the total sales in the two months. What do you conclude? Has
there been an increase in sales?
                                                    (1,056,144-866,243)
 Total sales increased 189,901 units or 21.9%.            866,243
Chapter 1: What is Statistics?


                    Exercises 1-d
                                The table below reports the number of
                                cars and light trucks sold by the Big
                                Three automobile manufacturers for
                                June 2004 and June 2005.




2. Compare the percent of the Big Three market for each company. Did the
market increase or did GM steal sales from the other companies? Cite
evidence.
Chapter 1: What is Statistics?


                    Exercises 1-d
                                The table below reports the number of
                                cars and light trucks sold by the Big
                                Three automobile manufacturers for
                                June 2004 and June 2005.




2. Compare the percent of the Big Three market for each company. Did the
market increase or did GM steal sales from the other companies? Cite
evidence.
 GM increased the market share by 9 percentage points from 43% to 52%.
 Crysler lost 3% and Ford lost 6%.
 All three companies increased the nubmer of units sold.

Weitere ähnliche Inhalte

Was ist angesagt?

Business Statistics Chapter 3
Business Statistics Chapter 3Business Statistics Chapter 3
Business Statistics Chapter 3Lux PP
 
Basic concepts of_econometrics
Basic concepts of_econometricsBasic concepts of_econometrics
Basic concepts of_econometricsSwapnaJahan
 
Chapter 6 simple regression and correlation
Chapter 6 simple regression and correlationChapter 6 simple regression and correlation
Chapter 6 simple regression and correlationRione Drevale
 
Uji chi square baru
Uji chi square baruUji chi square baru
Uji chi square baruRiswan
 
Binary OR Binomial logistic regression
Binary OR Binomial logistic regression Binary OR Binomial logistic regression
Binary OR Binomial logistic regression Dr Athar Khan
 
Regression Analysis
Regression AnalysisRegression Analysis
Regression AnalysisSalim Azad
 
Multiple Linear Regression
Multiple Linear RegressionMultiple Linear Regression
Multiple Linear RegressionIndus University
 
1 marshall hicks-slutsky
1 marshall hicks-slutsky1 marshall hicks-slutsky
1 marshall hicks-slutskyAnbul Tariq
 
Econometrics notes (Introduction, Simple Linear regression, Multiple linear r...
Econometrics notes (Introduction, Simple Linear regression, Multiple linear r...Econometrics notes (Introduction, Simple Linear regression, Multiple linear r...
Econometrics notes (Introduction, Simple Linear regression, Multiple linear r...Muhammad Ali
 
Multiple linear regression
Multiple linear regressionMultiple linear regression
Multiple linear regressionJames Neill
 
Hypothesis testing; z test, t-test. f-test
Hypothesis testing; z test, t-test. f-testHypothesis testing; z test, t-test. f-test
Hypothesis testing; z test, t-test. f-testShakehand with Life
 
Regression analysis
Regression analysisRegression analysis
Regression analysisRavi shankar
 
Hypothesis testing
Hypothesis testingHypothesis testing
Hypothesis testingiamkim
 
050 sampling theory
050 sampling theory050 sampling theory
050 sampling theoryRaj Teotia
 
Simple Linier Regression
Simple Linier RegressionSimple Linier Regression
Simple Linier Regressiondessybudiyanti
 
Regression analysis ppt
Regression analysis pptRegression analysis ppt
Regression analysis pptElkana Rorio
 

Was ist angesagt? (20)

Index number
Index numberIndex number
Index number
 
Business Statistics Chapter 3
Business Statistics Chapter 3Business Statistics Chapter 3
Business Statistics Chapter 3
 
Malhotra17
Malhotra17Malhotra17
Malhotra17
 
Econometrics chapter 8
Econometrics chapter 8Econometrics chapter 8
Econometrics chapter 8
 
Basic concepts of_econometrics
Basic concepts of_econometricsBasic concepts of_econometrics
Basic concepts of_econometrics
 
Chapter 6 simple regression and correlation
Chapter 6 simple regression and correlationChapter 6 simple regression and correlation
Chapter 6 simple regression and correlation
 
An Overview of Simple Linear Regression
An Overview of Simple Linear RegressionAn Overview of Simple Linear Regression
An Overview of Simple Linear Regression
 
Uji chi square baru
Uji chi square baruUji chi square baru
Uji chi square baru
 
Binary OR Binomial logistic regression
Binary OR Binomial logistic regression Binary OR Binomial logistic regression
Binary OR Binomial logistic regression
 
Regression Analysis
Regression AnalysisRegression Analysis
Regression Analysis
 
Multiple Linear Regression
Multiple Linear RegressionMultiple Linear Regression
Multiple Linear Regression
 
1 marshall hicks-slutsky
1 marshall hicks-slutsky1 marshall hicks-slutsky
1 marshall hicks-slutsky
 
Econometrics notes (Introduction, Simple Linear regression, Multiple linear r...
Econometrics notes (Introduction, Simple Linear regression, Multiple linear r...Econometrics notes (Introduction, Simple Linear regression, Multiple linear r...
Econometrics notes (Introduction, Simple Linear regression, Multiple linear r...
 
Multiple linear regression
Multiple linear regressionMultiple linear regression
Multiple linear regression
 
Hypothesis testing; z test, t-test. f-test
Hypothesis testing; z test, t-test. f-testHypothesis testing; z test, t-test. f-test
Hypothesis testing; z test, t-test. f-test
 
Regression analysis
Regression analysisRegression analysis
Regression analysis
 
Hypothesis testing
Hypothesis testingHypothesis testing
Hypothesis testing
 
050 sampling theory
050 sampling theory050 sampling theory
050 sampling theory
 
Simple Linier Regression
Simple Linier RegressionSimple Linier Regression
Simple Linier Regression
 
Regression analysis ppt
Regression analysis pptRegression analysis ppt
Regression analysis ppt
 

Ähnlich wie 001 Lesson 1 Statistical Techniques for Business & Economics

The role of statistics and the data analysis process.ppt
The role of statistics and the data analysis process.pptThe role of statistics and the data analysis process.ppt
The role of statistics and the data analysis process.pptJakeCuenca10
 
Thiyagu statistics
Thiyagu   statisticsThiyagu   statistics
Thiyagu statisticsThiyagu K
 
Sqqs1013 ch1-a122
Sqqs1013 ch1-a122Sqqs1013 ch1-a122
Sqqs1013 ch1-a122kim rae KI
 
statics engineering mechanics slides.pdf
statics engineering mechanics slides.pdfstatics engineering mechanics slides.pdf
statics engineering mechanics slides.pdfAurangzebRashidMasud2
 
Introduction to statistics.pptx
Introduction to statistics.pptxIntroduction to statistics.pptx
Introduction to statistics.pptxUnfold1
 
Analysing & interpreting data.ppt
Analysing & interpreting data.pptAnalysing & interpreting data.ppt
Analysing & interpreting data.pptmanaswidebbarma1
 
Lect 1_Biostat.pdf
Lect 1_Biostat.pdfLect 1_Biostat.pdf
Lect 1_Biostat.pdfBirhanTesema
 
STAT 1 - Basic-Concepts-in-Statistics.pptx
STAT 1 - Basic-Concepts-in-Statistics.pptxSTAT 1 - Basic-Concepts-in-Statistics.pptx
STAT 1 - Basic-Concepts-in-Statistics.pptxJerryJunCuizon
 
7jjjjjjjjjjjjjvcxzffghjknbvfhjknbvcduukkk
7jjjjjjjjjjjjjvcxzffghjknbvfhjknbvcduukkk7jjjjjjjjjjjjjvcxzffghjknbvfhjknbvcduukkk
7jjjjjjjjjjjjjvcxzffghjknbvfhjknbvcduukkkyeasmin75648
 
Meaning and Importance of Statistics
Meaning and Importance of StatisticsMeaning and Importance of Statistics
Meaning and Importance of StatisticsFlipped Channel
 
Introduce Statistics ppt
Introduce Statistics pptIntroduce Statistics ppt
Introduce Statistics pptJustynOwen
 

Ähnlich wie 001 Lesson 1 Statistical Techniques for Business & Economics (20)

001
001001
001
 
Lesson01
Lesson01Lesson01
Lesson01
 
Qm 0809
Qm 0809 Qm 0809
Qm 0809
 
The role of statistics and the data analysis process.ppt
The role of statistics and the data analysis process.pptThe role of statistics and the data analysis process.ppt
The role of statistics and the data analysis process.ppt
 
Thiyagu statistics
Thiyagu   statisticsThiyagu   statistics
Thiyagu statistics
 
Sqqs1013 ch1-a122
Sqqs1013 ch1-a122Sqqs1013 ch1-a122
Sqqs1013 ch1-a122
 
statistics Lesson 1
statistics Lesson 1statistics Lesson 1
statistics Lesson 1
 
Statistics.pptx
Statistics.pptxStatistics.pptx
Statistics.pptx
 
statics engineering mechanics slides.pdf
statics engineering mechanics slides.pdfstatics engineering mechanics slides.pdf
statics engineering mechanics slides.pdf
 
Introduction to statistics.pptx
Introduction to statistics.pptxIntroduction to statistics.pptx
Introduction to statistics.pptx
 
Adv.-Statistics-2.pptx
Adv.-Statistics-2.pptxAdv.-Statistics-2.pptx
Adv.-Statistics-2.pptx
 
Analysing & interpreting data.ppt
Analysing & interpreting data.pptAnalysing & interpreting data.ppt
Analysing & interpreting data.ppt
 
Chapter 1
Chapter 1Chapter 1
Chapter 1
 
Lect 1_Biostat.pdf
Lect 1_Biostat.pdfLect 1_Biostat.pdf
Lect 1_Biostat.pdf
 
STAT 1 - Basic-Concepts-in-Statistics.pptx
STAT 1 - Basic-Concepts-in-Statistics.pptxSTAT 1 - Basic-Concepts-in-Statistics.pptx
STAT 1 - Basic-Concepts-in-Statistics.pptx
 
chap1.ppt
chap1.pptchap1.ppt
chap1.ppt
 
7jjjjjjjjjjjjjvcxzffghjknbvfhjknbvcduukkk
7jjjjjjjjjjjjjvcxzffghjknbvfhjknbvcduukkk7jjjjjjjjjjjjjvcxzffghjknbvfhjknbvcduukkk
7jjjjjjjjjjjjjvcxzffghjknbvfhjknbvcduukkk
 
Meaning and Importance of Statistics
Meaning and Importance of StatisticsMeaning and Importance of Statistics
Meaning and Importance of Statistics
 
Introduce Statistics ppt
Introduce Statistics pptIntroduce Statistics ppt
Introduce Statistics ppt
 
Grade 7 Statistics
Grade 7 StatisticsGrade 7 Statistics
Grade 7 Statistics
 

Mehr von Ning Ding

Victor Yuan: interpretation of the economic data in China
Victor Yuan: interpretation of the economic data in ChinaVictor Yuan: interpretation of the economic data in China
Victor Yuan: interpretation of the economic data in ChinaNing Ding
 
Lesson 06 chapter 9 two samples test and Chapter 11 chi square test
Lesson 06 chapter 9 two samples test and Chapter 11 chi square testLesson 06 chapter 9 two samples test and Chapter 11 chi square test
Lesson 06 chapter 9 two samples test and Chapter 11 chi square testNing Ding
 
Lesson 04 chapter 7 estimation
Lesson 04 chapter 7 estimationLesson 04 chapter 7 estimation
Lesson 04 chapter 7 estimationNing Ding
 
Oct11 college 5
Oct11 college 5Oct11 college 5
Oct11 college 5Ning Ding
 
Lesson 05 chapter 8 hypothesis testing
Lesson 05 chapter 8 hypothesis testingLesson 05 chapter 8 hypothesis testing
Lesson 05 chapter 8 hypothesis testingNing Ding
 
Lesson 03 chapter 6 sampling
Lesson 03 chapter 6 samplingLesson 03 chapter 6 sampling
Lesson 03 chapter 6 samplingNing Ding
 
Sept27 college 3
Sept27 college 3Sept27 college 3
Sept27 college 3Ning Ding
 
Sept19 college 2
Sept19 college 2Sept19 college 2
Sept19 college 2Ning Ding
 
Lesson 02 class practices
Lesson 02 class practicesLesson 02 class practices
Lesson 02 class practicesNing Ding
 
Sept13 2011 college 1
Sept13 2011 college 1Sept13 2011 college 1
Sept13 2011 college 1Ning Ding
 

Mehr von Ning Ding (20)

Victor Yuan: interpretation of the economic data in China
Victor Yuan: interpretation of the economic data in ChinaVictor Yuan: interpretation of the economic data in China
Victor Yuan: interpretation of the economic data in China
 
Lesson 6
Lesson 6Lesson 6
Lesson 6
 
Lesson 5
Lesson 5Lesson 5
Lesson 5
 
Lesson 4
Lesson 4Lesson 4
Lesson 4
 
Lesson 3
Lesson 3Lesson 3
Lesson 3
 
Lesson 2
Lesson 2Lesson 2
Lesson 2
 
Lesson 1
Lesson 1Lesson 1
Lesson 1
 
Lesson 06 chapter 9 two samples test and Chapter 11 chi square test
Lesson 06 chapter 9 two samples test and Chapter 11 chi square testLesson 06 chapter 9 two samples test and Chapter 11 chi square test
Lesson 06 chapter 9 two samples test and Chapter 11 chi square test
 
Lesson 04 chapter 7 estimation
Lesson 04 chapter 7 estimationLesson 04 chapter 7 estimation
Lesson 04 chapter 7 estimation
 
Oct11 college 5
Oct11 college 5Oct11 college 5
Oct11 college 5
 
Lesson 05 chapter 8 hypothesis testing
Lesson 05 chapter 8 hypothesis testingLesson 05 chapter 8 hypothesis testing
Lesson 05 chapter 8 hypothesis testing
 
Lesson 03 chapter 6 sampling
Lesson 03 chapter 6 samplingLesson 03 chapter 6 sampling
Lesson 03 chapter 6 sampling
 
Sept27 college 3
Sept27 college 3Sept27 college 3
Sept27 college 3
 
Sept19 college 2
Sept19 college 2Sept19 college 2
Sept19 college 2
 
Lesson 02 class practices
Lesson 02 class practicesLesson 02 class practices
Lesson 02 class practices
 
Sept13 2011 college 1
Sept13 2011 college 1Sept13 2011 college 1
Sept13 2011 college 1
 
Lesson06
Lesson06Lesson06
Lesson06
 
Lesson05
Lesson05Lesson05
Lesson05
 
Lesson04
Lesson04Lesson04
Lesson04
 
Lesson03
Lesson03Lesson03
Lesson03
 

Kürzlich hochgeladen

Q-Factor HISPOL Quiz-6th April 2024, Quiz Club NITW
Q-Factor HISPOL Quiz-6th April 2024, Quiz Club NITWQ-Factor HISPOL Quiz-6th April 2024, Quiz Club NITW
Q-Factor HISPOL Quiz-6th April 2024, Quiz Club NITWQuiz Club NITW
 
Multi Domain Alias In the Odoo 17 ERP Module
Multi Domain Alias In the Odoo 17 ERP ModuleMulti Domain Alias In the Odoo 17 ERP Module
Multi Domain Alias In the Odoo 17 ERP ModuleCeline George
 
How to Make a Duplicate of Your Odoo 17 Database
How to Make a Duplicate of Your Odoo 17 DatabaseHow to Make a Duplicate of Your Odoo 17 Database
How to Make a Duplicate of Your Odoo 17 DatabaseCeline George
 
4.16.24 Poverty and Precarity--Desmond.pptx
4.16.24 Poverty and Precarity--Desmond.pptx4.16.24 Poverty and Precarity--Desmond.pptx
4.16.24 Poverty and Precarity--Desmond.pptxmary850239
 
Congestive Cardiac Failure..presentation
Congestive Cardiac Failure..presentationCongestive Cardiac Failure..presentation
Congestive Cardiac Failure..presentationdeepaannamalai16
 
Using Grammatical Signals Suitable to Patterns of Idea Development
Using Grammatical Signals Suitable to Patterns of Idea DevelopmentUsing Grammatical Signals Suitable to Patterns of Idea Development
Using Grammatical Signals Suitable to Patterns of Idea Developmentchesterberbo7
 
Oppenheimer Film Discussion for Philosophy and Film
Oppenheimer Film Discussion for Philosophy and FilmOppenheimer Film Discussion for Philosophy and Film
Oppenheimer Film Discussion for Philosophy and FilmStan Meyer
 
Student Profile Sample - We help schools to connect the data they have, with ...
Student Profile Sample - We help schools to connect the data they have, with ...Student Profile Sample - We help schools to connect the data they have, with ...
Student Profile Sample - We help schools to connect the data they have, with ...Seán Kennedy
 
BIOCHEMISTRY-CARBOHYDRATE METABOLISM CHAPTER 2.pptx
BIOCHEMISTRY-CARBOHYDRATE METABOLISM CHAPTER 2.pptxBIOCHEMISTRY-CARBOHYDRATE METABOLISM CHAPTER 2.pptx
BIOCHEMISTRY-CARBOHYDRATE METABOLISM CHAPTER 2.pptxSayali Powar
 
MS4 level being good citizen -imperative- (1) (1).pdf
MS4 level   being good citizen -imperative- (1) (1).pdfMS4 level   being good citizen -imperative- (1) (1).pdf
MS4 level being good citizen -imperative- (1) (1).pdfMr Bounab Samir
 
How to Fix XML SyntaxError in Odoo the 17
How to Fix XML SyntaxError in Odoo the 17How to Fix XML SyntaxError in Odoo the 17
How to Fix XML SyntaxError in Odoo the 17Celine George
 
Grade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdf
Grade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdfGrade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdf
Grade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdfJemuel Francisco
 
Measures of Position DECILES for ungrouped data
Measures of Position DECILES for ungrouped dataMeasures of Position DECILES for ungrouped data
Measures of Position DECILES for ungrouped dataBabyAnnMotar
 
Unraveling Hypertext_ Analyzing Postmodern Elements in Literature.pptx
Unraveling Hypertext_ Analyzing  Postmodern Elements in  Literature.pptxUnraveling Hypertext_ Analyzing  Postmodern Elements in  Literature.pptx
Unraveling Hypertext_ Analyzing Postmodern Elements in Literature.pptxDhatriParmar
 
Grade Three -ELLNA-REVIEWER-ENGLISH.pptx
Grade Three -ELLNA-REVIEWER-ENGLISH.pptxGrade Three -ELLNA-REVIEWER-ENGLISH.pptx
Grade Three -ELLNA-REVIEWER-ENGLISH.pptxkarenfajardo43
 
4.11.24 Poverty and Inequality in America.pptx
4.11.24 Poverty and Inequality in America.pptx4.11.24 Poverty and Inequality in America.pptx
4.11.24 Poverty and Inequality in America.pptxmary850239
 
Q4-PPT-Music9_Lesson-1-Romantic-Opera.pptx
Q4-PPT-Music9_Lesson-1-Romantic-Opera.pptxQ4-PPT-Music9_Lesson-1-Romantic-Opera.pptx
Q4-PPT-Music9_Lesson-1-Romantic-Opera.pptxlancelewisportillo
 
INTRODUCTION TO CATHOLIC CHRISTOLOGY.pptx
INTRODUCTION TO CATHOLIC CHRISTOLOGY.pptxINTRODUCTION TO CATHOLIC CHRISTOLOGY.pptx
INTRODUCTION TO CATHOLIC CHRISTOLOGY.pptxHumphrey A Beña
 
DIFFERENT BASKETRY IN THE PHILIPPINES PPT.pptx
DIFFERENT BASKETRY IN THE PHILIPPINES PPT.pptxDIFFERENT BASKETRY IN THE PHILIPPINES PPT.pptx
DIFFERENT BASKETRY IN THE PHILIPPINES PPT.pptxMichelleTuguinay1
 
Reading and Writing Skills 11 quarter 4 melc 1
Reading and Writing Skills 11 quarter 4 melc 1Reading and Writing Skills 11 quarter 4 melc 1
Reading and Writing Skills 11 quarter 4 melc 1GloryAnnCastre1
 

Kürzlich hochgeladen (20)

Q-Factor HISPOL Quiz-6th April 2024, Quiz Club NITW
Q-Factor HISPOL Quiz-6th April 2024, Quiz Club NITWQ-Factor HISPOL Quiz-6th April 2024, Quiz Club NITW
Q-Factor HISPOL Quiz-6th April 2024, Quiz Club NITW
 
Multi Domain Alias In the Odoo 17 ERP Module
Multi Domain Alias In the Odoo 17 ERP ModuleMulti Domain Alias In the Odoo 17 ERP Module
Multi Domain Alias In the Odoo 17 ERP Module
 
How to Make a Duplicate of Your Odoo 17 Database
How to Make a Duplicate of Your Odoo 17 DatabaseHow to Make a Duplicate of Your Odoo 17 Database
How to Make a Duplicate of Your Odoo 17 Database
 
4.16.24 Poverty and Precarity--Desmond.pptx
4.16.24 Poverty and Precarity--Desmond.pptx4.16.24 Poverty and Precarity--Desmond.pptx
4.16.24 Poverty and Precarity--Desmond.pptx
 
Congestive Cardiac Failure..presentation
Congestive Cardiac Failure..presentationCongestive Cardiac Failure..presentation
Congestive Cardiac Failure..presentation
 
Using Grammatical Signals Suitable to Patterns of Idea Development
Using Grammatical Signals Suitable to Patterns of Idea DevelopmentUsing Grammatical Signals Suitable to Patterns of Idea Development
Using Grammatical Signals Suitable to Patterns of Idea Development
 
Oppenheimer Film Discussion for Philosophy and Film
Oppenheimer Film Discussion for Philosophy and FilmOppenheimer Film Discussion for Philosophy and Film
Oppenheimer Film Discussion for Philosophy and Film
 
Student Profile Sample - We help schools to connect the data they have, with ...
Student Profile Sample - We help schools to connect the data they have, with ...Student Profile Sample - We help schools to connect the data they have, with ...
Student Profile Sample - We help schools to connect the data they have, with ...
 
BIOCHEMISTRY-CARBOHYDRATE METABOLISM CHAPTER 2.pptx
BIOCHEMISTRY-CARBOHYDRATE METABOLISM CHAPTER 2.pptxBIOCHEMISTRY-CARBOHYDRATE METABOLISM CHAPTER 2.pptx
BIOCHEMISTRY-CARBOHYDRATE METABOLISM CHAPTER 2.pptx
 
MS4 level being good citizen -imperative- (1) (1).pdf
MS4 level   being good citizen -imperative- (1) (1).pdfMS4 level   being good citizen -imperative- (1) (1).pdf
MS4 level being good citizen -imperative- (1) (1).pdf
 
How to Fix XML SyntaxError in Odoo the 17
How to Fix XML SyntaxError in Odoo the 17How to Fix XML SyntaxError in Odoo the 17
How to Fix XML SyntaxError in Odoo the 17
 
Grade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdf
Grade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdfGrade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdf
Grade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdf
 
Measures of Position DECILES for ungrouped data
Measures of Position DECILES for ungrouped dataMeasures of Position DECILES for ungrouped data
Measures of Position DECILES for ungrouped data
 
Unraveling Hypertext_ Analyzing Postmodern Elements in Literature.pptx
Unraveling Hypertext_ Analyzing  Postmodern Elements in  Literature.pptxUnraveling Hypertext_ Analyzing  Postmodern Elements in  Literature.pptx
Unraveling Hypertext_ Analyzing Postmodern Elements in Literature.pptx
 
Grade Three -ELLNA-REVIEWER-ENGLISH.pptx
Grade Three -ELLNA-REVIEWER-ENGLISH.pptxGrade Three -ELLNA-REVIEWER-ENGLISH.pptx
Grade Three -ELLNA-REVIEWER-ENGLISH.pptx
 
4.11.24 Poverty and Inequality in America.pptx
4.11.24 Poverty and Inequality in America.pptx4.11.24 Poverty and Inequality in America.pptx
4.11.24 Poverty and Inequality in America.pptx
 
Q4-PPT-Music9_Lesson-1-Romantic-Opera.pptx
Q4-PPT-Music9_Lesson-1-Romantic-Opera.pptxQ4-PPT-Music9_Lesson-1-Romantic-Opera.pptx
Q4-PPT-Music9_Lesson-1-Romantic-Opera.pptx
 
INTRODUCTION TO CATHOLIC CHRISTOLOGY.pptx
INTRODUCTION TO CATHOLIC CHRISTOLOGY.pptxINTRODUCTION TO CATHOLIC CHRISTOLOGY.pptx
INTRODUCTION TO CATHOLIC CHRISTOLOGY.pptx
 
DIFFERENT BASKETRY IN THE PHILIPPINES PPT.pptx
DIFFERENT BASKETRY IN THE PHILIPPINES PPT.pptxDIFFERENT BASKETRY IN THE PHILIPPINES PPT.pptx
DIFFERENT BASKETRY IN THE PHILIPPINES PPT.pptx
 
Reading and Writing Skills 11 quarter 4 melc 1
Reading and Writing Skills 11 quarter 4 melc 1Reading and Writing Skills 11 quarter 4 melc 1
Reading and Writing Skills 11 quarter 4 melc 1
 

001 Lesson 1 Statistical Techniques for Business & Economics

  • 1. IBS Statistics Year 1 Dr. Ning DING n.ding@pl.hanze.nl I007, Friday & Monday
  • 2. Table of content • Chapter 1: What is statistics? – Why study statistics? – What is meant by statistics? – Types of statistics – Types of variables – Levels of measurement • Norminal-Level Data • Ordinal-Level Data • Interval-Level Data – Ethics and Statistics • Chapter 2: Describing data – Frequency tables – Frequency distributions – Graphic presentation
  • 3. Learning Goals • Chapter 1: What is statistics? – Understand why we study statistics – Explain what is meant by descriptive and inferential statistics – Distinguish between a qualitative and quantitative variable – Describe how a discrete variable is different from a continous variable – Distinguish among the nominal, ordinal, interval and ratio levels of measurement • Chapter 2: Describing data – Organize qualitative data into a frequency table – Present a frequency table as a bar chart or a pie chart – Organize quantitative data into a freqency distribution – Present a frequency distribution for quantitative data using histograms, frequency polygons, and cumulative frequency polygons.
  • 4. Chapter 1: What is Statistics? 1. Introduction Statistics are everywhere.
  • 5. Chapter 1: What is Statistics? 1. Introduction
  • 6. Chapter 1: What is Statistics? 1. Introduction Statistics help you make decisions.
  • 7. Chapter 1: What is Statistics? 1. Introduction Statistics give you a better understanding.
  • 8. Chapter 1: What is Statistics? 1. Introduction 1. Adequate information? Additional information? 2. No misleading information? 3. Summarize the information. 4. Analyze available information. 5. Conclusions!
  • 9. Chapter 1: What is Statistics? 1. Introduction Statistics: The science of collecting, organizing, presenting, analyzing and interpreting data to assist in making more effective decisions.
  • 10. Chapter 1: What is Statistics? 1. Introduction Making decisions Interpret data Present data Analyze data Organize data Collect data
  • 11. Chapter 1: What is Statistics? 2. Types of Statistics Descriptive Statistics: Methods of organizing, summarizing and presenting data in an informative way. Inferential Statistics: Methods used to estimate a property of a population on the basis of a sample.
  • 12. Chapter 1: What is Statistics? 2. Types of Statistics Descriptive Inferential Statistics: Statistics:
  • 13. Chapter 1: What is Statistics? 2. Types of Statistics Population: The entire set of individual or objects of interest or the measurements obtained from all individuals or objects of interest. Sample: A portion, or part, of the population of interest.
  • 14. Chapter 1: What is Statistics? 2. Types of Statistics Population: Sample: Play
  • 15. Chapter 1: What is Statistics? 3. Types of Variables Qualitative: nonnumeric, attribute Quantitative: numerical
  • 16. Chapter 1: What is Statistics? 3. Types of Variables Quantitative: Qualitative:
  • 17. Chapter 1: What is Statistics? 3. Types of Variables Discrete counting or Continuous measuring
  • 18. Chapter 1: What is Statistics? 4. Levels of Measurement Nominal: •Data categories are represented by labels or names. •Even when the labels are numerically coded, the data categories have no logical order. •Example: •Eye colour, gender, religious affiliation Ordinal: •Data classifications are represented by sets of labels or names (high, medium, low) that have relative values. •Because of the relative values, the data classified can be ranked or ordered. •Example: •During a taste test of 4 soft drinks, Mellow Yellow was ranked number 1, Sprite number 2, Seven-up number 3, and Orange Crush number 4.
  • 19. Chapter 1: What is Statistics? 4. Levels of Measurement Nominal: Ordinal: No logical order Ranked or ordered
  • 20. Chapter 1: What is Statistics? 4. Levels of Measurement Interval: •Similar to the ordinal level, with the additional property that meaningful amounts of differences between data values can be determined. •There is no natural zero point. •Example: •Temperature on the Fahrenheit scale. Ratio: •The interval level with an inherent zero starting point. •Differences and ratios are meaningful for this level of measurement. •Examples: •Monthly income; distance travelled by manufacturer’s representatives per month.
  • 21. Chapter 1: What is Statistics? 4. Levels of Measurement Online Animation Nominal: Ordinal: Interval: Ordered, Equal differences Ratio: Zero
  • 22. vels of Measurement Chapter 1: What is Statistics? 4. Levels of Measurement
  • 23. Chapter 1: What is Statistics? Exercises 1-a For each of the following, determine whether the group is a sample or a population. •The participants in a study of a new cholesterol drug. Sample •The drivers who received a speeding ticket Kansas City last month. Population •Those on welfare in Cook County (Chicago), Illinois. Population •The 30 stocks reported as a part of the Dow Jones Industrial Average. Sample P14. N.4 Ch.1
  • 24. Chapter 1: What is Statistics? Exercises 1-b Refer to the Real Estate data at the back of the text, which report information on homes sold in the Denver, Colorado, area last year. Consider the following variables: selling price, number of bedrooms, township, and distance from the center of the city. •Which of the variables are qualitative and which are quantitative? township all the rest… •Determin the level of measurement for each of the variables. Township = nominal level All the rest…=ratio P18. N.16 Ch.1
  • 25. Chapter 2: Describing data 2.1 Frequency Table Frequency Table: •A grouping of qualitative data into mutually exclusive classes showing the number of observations in each class. Example: Ice cream 20 vendors Choco 6 7 5 7 7 8 7 6 9 7 Vanilla 4 10 6 8 8 9 5 6 4 8
  • 26. Chapter 2: Describing data 2.1 Frequency Table Relative Class Frequencies: •Show the fraction of the total number of observations in each class Example: Ice cream 20 vendors Choco 6 7 5 7 7 8 7 6 9 7 Vanilla 4 10 6 8 8 9 5 6 4 8
  • 27. Chapter 1: What is Statistics? Exercises 2-a A total of 1,000 residents in Minnesota were asked which season they preferred. The results were 100 liked winter best, 300 liked spring, 400 liked summer, and 200 liked fall. If the data were summarized in a frequency table, how many classes would be used? What would be the relative frequencies for each class? P27. N.3 .Ch.2
  • 28. Chapter 2: Describing data 2.2 Graphic Presentation of Qualitative Data Bar Chart: •The classes are reported on the horizontal axis •The class frequencies on the vertical axis •The class frequencies are proportional to the heights of the bars. Example: Ice cream 20 vendors Ice Cream Sales 70 Choco, 69 Vanilla, 68 65 Choco Axis 60 Vanilla 55 50 Choco Vanilla Types
  • 29. Chapter 2: Describing data 2.2 Graphic Presentation of Qualitative Data Pie Chart: •Shows the proportion or percent that each class represents of the total number of frequencies Example: Ice cream 20 vendors 49.64% 50.36% 1 2
  • 30. Chapter 2: Describing data 2. Frequency Distribution Frequency Distribution: •A grouping of data into mutually exclusive classes showing the number of observations in each class.
  • 31. Chapter 2: Describing data 2. Frequency Distribution Frequency Distribution: •A grouping of data into mutually exclusive classes showing the number of observations in each class.
  • 32. Chapter 2: Describing data 2. Frequency Distribution Step 1: Just enough recipe 2 to the k rule N=27 number of class=5 Step 2: Class Interval 10 -< 20 4 20 -< 30 1 (55-14)/5 ≈ 8 30 -< 40 10 Step 3: Choose nice “round” boundaries 40 -< 50 9 Step 4: Try to avoid empty and open classes 50 -< 60 3 N=27 Practice
  • 33. Chapter 2: Describing data Exercises 2-b A set of data consists of 45 observations between $0 and $29. What size would you recommend for the class interval? 25 = 32, 26 = 64, suggests 6 classes i> $30 - $0 =5 6 Use interval of 5 P33. N.8 .Ch.2
  • 34. Chapter 2: Describing data Exercises 2-b The Quick Change Oil Company has a number of outlets in the metropolitan Seattle area. The daily number of oil changes at the Oak Street outlet in the past 20 days are: 65 98 55 62 79 59 51 90 72 56 70 62 66 80 94 79 63 73 71 85 a. How many classes would you recommend? a. 24 = 16, 25 = 32, suggests 5 classes b. What class interval would you suggest? 99 - 51 i> ≈ 9 b. Use interval of 10 5 P34. N.12.Ch.2
  • 35. Chapter 2: Describing data Exercises 2-b The Quick Change Oil Company has a number of outlets in the metropolitan Seattle area. The daily number of oil changes at the Oak Street outlet in the past 20 days are: 65 98 55 62 79 59 51 90 72 56 70 62 66 80 94 79 63 73 71 85 c. What lower limit would you recommend for the first class? c. 50 P34. N.12.Ch.2
  • 36. Chapter 2: Describing data 3. Graphic Presentation Histogram •The classes are marked on the horizontal axis •The class frequencies on the vertical axis •The class frequencies are represented by the heights of the bars and the bars are adjacent to each other. Polygon: •The shape of a distribution •Similar to a histogram
  • 37. Chapter 2: Describing data 3. Graphic Presentation Histogram Example: 16 Amount of € spent on books by 50 students 14 12 No. of students 10 8 6 4 2 0 25 75 125 175 225 275 325 375 425 Amount in €
  • 38. Chapter 2: Describing data 3. Graphic Presentation Polygon Example: Amount of € spent on books by 50 students 16 14 12 No. of students 10 8 6 4 2 0 125 175 225 275 325 375 425 Amount in €
  • 39. Chapter 2: Describing data 3. Graphic Presentation Cumulative frequency distribution: used to determine how many or what proportion of the data values are below or above a certain value. Amount of € spent on books by 50 students 60 50 Cumulative frequency 40 30 20 10 0 100 150 200 250 300 350 400 450 Amount in €
  • 40. Chapter 2: Describing data 3. Graphic Presentation
  • 41. Chapter 1: What is Statistics? Summary • Chapter 1: What is statistics? – Understand why we study statistics – Explain what is meant by descriptive and inferential statistics – Distinguish between a qualitative and quantitative variable – Describe how a discrete variable is different from a continous variable – Distinguish among the nominal, ordinal, interval and ratio levels of measurement • Chapter 2: Describing data – Organize qualitative data into a frequency table – Present a frequency table as a bar chart or a pie chart – Organize quantitative data into a freqency distribution – Present a frequency distribution for quantitative data using histograms, frequency polygons, and cumulative frequency polygons.
  • 42. Chapter 1: What is Statistics? Exercises 1-a What is the level of measurement for each of the following variables? • A. student IQ ratings Interval • B. distance students travel to class Ratio • C. student scores on the first statistics test Interval • D. a classification of students by state of birth Nominal • E. a ranking of students as freshmen, sophomore, junior, and senior Ordinal • F. Number of hours students study per week Ratio
  • 43. Chapter 1: What is Statistics? Exercises 1-b Place these variables in the following classification tables. a. Salary b. Gender Discrete Continuous c. Sales volumen of b. Gender d. Soft drink preference MP3 players Qualitative d. Soft drink preference e. Temperature f. SAT scores f. SAT scores a. Salary g. Student rank g. Student rank in class c. Sales volume of MP3 players in class Quantitative h. Rating of a h. Rating of a finance professor e. Temperature finance professor i. Number of home computers i. Number of home computers P16. N.9 Ch.1
  • 44. Chapter 1: What is Statistics? Exercises 1-c Place these variables in the following classification tables. a. Salary b. Gender Discrete Continuous c. Sales volumen of b. Gender MP3 players Nominal d. Soft drink preference d. Soft drink preference e. Temperature Ordinal f. SAT scores g. Student rank in class h. Rating of a finance professor g. Student rank in class f. SAT scores e. Temperature h. Rating of a Interval finance a. Salary professor i. Number of Ratio c. Sales volume of MP3 players home computers i. Number of home computers
  • 45. Chapter 1: What is Statistics? Exercises 1-d The table below reports the number of cars and light trucks sold by the Big Three automobile manufacturers for June 2004 and June 2005. 1. Compare the total sales in the two months. What do you conclude? Has there been an increase in sales? P17. N.13 Ch.1
  • 46. Chapter 1: What is Statistics? Exercises 1-d The table below reports the number of cars and light trucks sold by the Big Three automobile manufacturers for June 2004 and June 2005. 1. Compare the total sales in the two months. What do you conclude? Has there been an increase in sales? (1,056,144-866,243) Total sales increased 189,901 units or 21.9%. 866,243
  • 47. Chapter 1: What is Statistics? Exercises 1-d The table below reports the number of cars and light trucks sold by the Big Three automobile manufacturers for June 2004 and June 2005. 2. Compare the percent of the Big Three market for each company. Did the market increase or did GM steal sales from the other companies? Cite evidence.
  • 48. Chapter 1: What is Statistics? Exercises 1-d The table below reports the number of cars and light trucks sold by the Big Three automobile manufacturers for June 2004 and June 2005. 2. Compare the percent of the Big Three market for each company. Did the market increase or did GM steal sales from the other companies? Cite evidence. GM increased the market share by 9 percentage points from 43% to 52%. Crysler lost 3% and Ford lost 6%. All three companies increased the nubmer of units sold.