research

1. Sampling Methods
Types and Techniques

2. SAMPLING
The sample population refers to the people who will actually take part in the study.
TWO TYPES OF SAMPLING
● PROBABILITY SAMPLING - random selection; allows you to make strong
statistical inferences about the entire group.
● NON-PROBABILITY SAMPLING - entails making non-random selections
based on convenience or other criteria to make data collection easier.

3. Population vs sample
● The population refers to the total group
about which you want to draw
conclusions.
- Geographic location, age, wealth,
and a variety of other criteria can all
be used to define the population.
● The sample is the group of people from
whom you will gather information.

4. ● SAMPLING FRAME
○ The sampling frame is the list of people from which the sample will be selected. It
should ideally cover the entire target demographic (and nobody who is not part of
that population).
● SAMPLE SIZE
○ The number of individuals you should include in your sample is determined by a
number of criteria, including the population's size and variability, as well as your
research design. Depending on what you want to achieve with statistical analysis,
there are numerous sample size calculators and formulas.

5. PROBABILITY SAMPLING
Every member of the population has
a possibility of being chosen in
probability sampling.
It's mostly employed in quantitative
studies.
Probability sampling techniques are
the best option for producing findings
that are representative of the
entire population.

6. NON-PROBABILITY SAMPLING
● chosen based on non-random
criteria
● not every individual has a
chance of being included.
● has a higher risk of sampling
bias
● still aim to make it as
representative of the
population as possible

7. 1. Convenience sampling
A convenience sample is made up of people who are most easily accessible to the
researcher.
2. Voluntary response sampling
A voluntary response sample is mostly dependent on ease of access
People volunteer themselves rather than the researcher selecting and contacting
individuals

8. 3. Purposive sampling
This sort of sampling, also known as judgment sampling, entails the researcher
utilizing their knowledge to choose a sample that is most relevant to the research's
purposes.
4. Snowball sampling
If the population is hard to access, snowball sampling can be used to recruit
participants via other participants.

9. Descriptive Statistics
Definitions, Types, Examples

10. ● Descriptive statistics summarize and organize
characteristics of a data set.
● A data set is a collection of responses or observations
from a sample or entire population.

11. Types of descriptive statistics
● The distribution concerns the frequency of each value.
● The central tendency concerns the averages of the
values.
● The variability or dispersion concerns how spread out the
values are.

12. Frequency distribution
A data set is made up of a distribution of values, or scores.
In tables or graphs, you can summarize the frequency of every
possible value of a variable in numbers or percentages.

13. Simple frequency distribution table
For the variable of gender, you
list all possible answers on the
left hand column. You count the
number or percentage of
responses for each answer and
display it on the right hand
column.
Gender Number
Male 182
Female 235
Other 27

14. Grouped frequency distribution table
In a grouped frequency
distribution, you can group
numerical response values and
add up the number of responses
for each group. You can also
convert each of these numbers
to percentages.
Library visits in the
past year
Percent
0–4 6%
5–8 20%
9–12 42%
13–16 24%
17+ 8%

15. Measures of central tendency
Measures of central tendency estimate the center, or
average, of a data set. The mean, median and mode are
3 ways of finding the average.

16. Mean
The mean, or M, is the most commonly used method for finding the
average.
Mean number of library visits
MEAN
Data set 15, 3, 12, 0, 24, 3
Sum of all values 15 + 3 + 12 + 0 + 24 + 3 = 57
Total number of responses N = 6
Mean Divide the sum of values by N to find M: 57/6 = 9.5

17. Median
The median is the value that’s exactly in the middle of a data set.
Median number of library visits
Ordered data set 0, 3, 3, 12, 15, 24
Middle numbers 3, 12
Median Find the mean of the two middle numbers: (3 + 12)/2 = 7.5

18. Mode
The mode is the simply the most popular or most frequent
response value. A data set can have no mode, one mode, or more
than one mode.
Mode number of library visits
Ordered data set 0, 3, 3, 12, 15, 24
Mode Find the most frequently occurring response: 3

19. Measures of variability
Measures of variability give you a sense of how spread out
the response values are. The range, standard deviation
and variance each reflect different aspects of spread.

20. Range
The range gives you an idea of how far apart the most extreme response
scores are. To find the range, simply subtract the lowest value from the
highest value.
Range of visits to the library in the past year
Ordered data set: 0, 3, 3, 12, 15, 24
Range: 24 – 0 = 24

21. References:
Bhandari, P. (2022, January 31). An introduction to descriptive statistics. Scribbr.
https://www.scribbr.com/statistics/descriptive-statistics/
McCombes, S. (2022, May 3). An introduction to sampling methods. Scribbr.
https://www.scribbr.com/methodology/sampling-methods/

22. References:
Bhandari, P. (2022, January 31). An introduction to descriptive statistics. Scribbr.
https://www.scribbr.com/statistics/descriptive-statistics/
McCombes, S. (2022, May 3). An introduction to sampling methods. Scribbr.
https://www.scribbr.com/methodology/sampling-methods/