CONDUCTING HYPOTHESIS TEST USING CLASSICAL( Critical Value) METHOD(ONE –SAMPLE CASE)

1. MR. FLORIAN E. MANZANILLA
DEMO TEACHING

2. CONDUCTING HYPOTHESIS TEST USING
CLASSICAL( Critical Value) METHOD
(ONE –SAMPLE CASE)
I. OBJECTIVES
A. Content Standards The learner demonstrates understanding of
key concepts of tests of hypotheses on the
population mean and population proportion.
B. Performance Standards The learner is able to perform appropriate tests of
hypotheses involving the population mean and
population proportion to make inferences in real-life
problems in different disciplines
C. Learning
Competencies/Objectives
At the end of the session, learners are expected to
1. Understand the underlying procedures in
Hypothesis testing
2. Conduct a statistical test using the Critical value or
classical method for one-sample case

3. ACTIVITY SHEET # 1.
Read the following statements. Choose the letter of the
best answer.
1. An Intelligent guess about the characteristics of a
population is called:
2. The important numerical value in hypothesis
testing is: a. parameter
c. hypothesis
3. Under the normal curve, the middle part represents:
b. acceptance region
c. 0.05
5. Which of the following serves as a guide in deciding
whether to reject or accept Ho : b. Decision rule

4. 6. Under the normal curve, when lines are drawn through
this value, they separate the rejection region from the
acceptance region
a. -1.645
b. 0.01
10. Which of the following best represents a set of
numerical data? c. variance
a. confidence coefficient
8. In hypothesis testing, the probability of committing
an error in rejecting a null hypothesis that is true is
denoted by:

5. Central Limit Theorem (CLT)
Accepting or Rejecting the Null Hypothesis
Making decision to accept or reject the
hypothesis depends on the test statistic value
compared with the confidence coefficient (critical
values)
It states in part, that as sample size increases,
the sampling distribution of the mean
approaches the normal distribution provided that
the sampling is random.

6. ELEMENTS OF HYPOTHESIS TESTING
1. Statistical hypothesis is an assumption about
a population parameter.
null hypothesis - it is hypothesis that there is
no significant difference between specified
populations. Denoted by : Ho

7. ELEMENTS OF HYPOTHESIS TESTING
2. Significance Level is the probability of making
Type I error

8. ELEMENTS OF HYPOTHESIS TESTING
3. Type of
Test

9. ELEMENTS OF HYPOTHESIS TESTING
4. Critical values of Z

10. ELEMENTS OF HYPOTHESIS TESTING

11. THE STEPS IN HYPOTHESIS TESTING
USING THE CLASSICAL
(CRITICAL VALUE) METHOD
STEPS
1. Formulate the
hypothesis
3. Select appropriate
test statistic
Ho and H1 , the two statements should be
formulated in such a way that if one is
true, the other is necessarily false)
(If the level of significance is not
identified it will always be set to be at .
05)

12. THE STEPS IN HYPOTHESIS TESTING
USING THE CLASSICAL
(CRITICAL VALUE) METHOD
STEPS
4. Establish the
critical region
5. Compute for the value of
the statistical test.
6. Make a decision and,
if possible draw a
conclusion
Depending on the type of alternative
hypothesis, the critical region may be lying
entirely on one tail or split into two equal parts
on both tails of the distribution.
Identify all the given and substitute to
the appropriate statistic to find the value.
(if the CV is within the region of rejection,
we reject Ho and accept H1, if it lies
outside the region of rejection, we accept
Ho)

13. EXAMPLE # 1

14. Solutions
STEPS ANSWERS
1. Formulate the
hypothesis
3. Select appropriate
test statistic

15. SOLUTIONS:
STEPS
4. Establish the
critical region
5. Compute for the value of
the statistical test.
6. Make a decision and,
if possible draw a
conclusion
Z >1.96 or Z < -1.96
The computed value of z is outside the region
of rejection (-1.33 > -1.96). Therefore, we may
accept the Ho. There is enough evidence
to support the claim of the manufacturer that
the average life of the bulbs it produces is
1000 hours.

16. Base from the examples that we have, What…
1.are the elements of hypothesis testing that
we need to understand?
2. are the procedure/steps underlying the
test of hypothesis.
3. generalization can you make regarding
hypothesis testing?
ABSTRACTION AND GENERALIZATION

17. EVALUATION :

18. “ There are two possible outcomes:
if the result confirms the hypothesis,
then you've made a measurement.
If the result is contrary to the
hypothesis, then you've made a
discovery.”
~ Enrico Fermi
CLOSURE