This document outlines the process of hypothesis testing. It begins with defining key terms like the null hypothesis (H0), alternative hypothesis (H1), significance level, test statistic, critical value, and decision rule. It then explains the steps involved: 1) setting up H0 and H1, 2) choosing a significance level, 3) calculating the test statistic, 4) finding the critical value, and 5) making a decision by comparing the test statistic and critical value. The overall goal of hypothesis testing is to evaluate claims about a population parameter based on a sample's data.

1. PRESENTED BY
SAHANA. B H
1ST M.Com
 Under the guidance of
 Sundar B. N.
 Asst. Prof. & Course Co-ordinator
 GFGCW, PG Studies in Commerce
 Holenarasipura

2.  Introduction
 Meaning
 Steps to be involved in testing of hypothesis
 Conclusion
 Bibliography

3. Hypothesis testing is an essential procedure in
Statistics. A hypothesis test evaluates two
Mutually exclusive statements about population
To determine which statement is best supported
By the sample data.

4. Hypothesis testing is an act in statistics whereby
An analyst test , an assumption regarding a
Population parameter.
“ A premise or claim that we want to test or
investigate”.
A Statistical hypothesis is a hypothesis that is
testable on the basis of observed data model as
realized values taken by a collection of random
variables.

5. 1. Setup null (H0) and alternative (H1) hypothesis
2. Decide the level of significance .
3. Calculate the test statistics.
4. Obtain the tabulated value .
5. Decision.

7. VALUE Ɵ0 OF PARAMETER
Ɵ0
PARAMETER OF TWO
POPULATION OF
INTEREST.
 H0:Ɵ=Ɵ0 and H1:Ɵ≠Ɵ0
(2TAILED TEST)
 H0:Ɵ≤Ɵ0 & H1:Ɵ>Ɵ0
 H0:Ɵ≥Ɵ0 & H1: Ɵ<Ɵ0
(1 TAILED TEST)
 H0:Ɵ1= Ɵ2 & H1 :Ɵ1≠Ɵ2
( 2 tailed)
 H0:Ɵ1≤02 &H1:Ɵ1>Ɵ2
 H0:Ɵ1≥02 & H1:Ɵ1<Ɵ2
 (1 tailed)

8. NULL HYPOTHESIS
ALTERNATIVE
HYPOTHESIS
 H0 is currently accepted value for
a papaparameter.
Ex; It is believed that a candy machine
chocolate bars that are on average 5g. A
worker claims that the machine after
maintenance no longer makes 5g. Bars.
Write H0 and H1.
 It’s also called research
hypothesis it involves the
claim to be tested.
Denoted as H1.
 Solution; H0;m is equal
to 5g.
H1; m is not
equal to 5g.

9.  Generally alpha is provided in problem of
hypothesis.
 If alpha is not specified then take 5% is usually
assumed .(0.05)
The significance level for given hypothesis test is a
value for which p values less than or equal to
considered statistically significant.
for example : In an upper tailed z test if a=0.05 than
the critical value is z=1.645.

10.  Another interpretation of significance level
‘based in decision theory, is that corresponds to
the value for which one chooses to reject or
accept the null hypothesis. The probability that
this is a mistake – the null hypothesis is true
when z statistic-is less than 0.01 in decision
theory this is known as type 1 error. The
probability of type 1 error is equal to significance
level’, the probability of rejecting H0 when it’s
fact falls is equal to 1 to minimize the probability
of type 1 error , the significance level is generally
choosen to be small.

11.  Formula :
 Test statistic = sample statistic-
parameter/standard error of sample statistic.
 its also known as calculated value of the test statistic)
 Ex: the mean life of particular battery is 75hr. A
sample of 9 bulbs is chosen and found to have S D.of
10hr”s and mean of 80 hrs . Find test statistic.
 T= 80-75/10 (9)
 =5/3.333
Answer:=1.5

12. It’s a tabulated value of the test statistic which can be
obtained from the corresponding standard table.
According to given ά and tails of the test.
When the sampling distribution of the statistic is
normal or nearly normal that critical value can be
expressed as a T score or a z score. To find a critical
value follow these steps.
1. Compute alpha (a). a=1-(confidence level /100)
2. Find the critical probability (p*)’p*=1-a/2.
3. To express the citical value as a z score, find the z
score having a cumulative probability equal to the
critical probability (p*).

14.  Find the degrees of freedom (df). Often, df is
equal to the sample size -1
 The critical t statistic (t*) is the t statistic having
degrees of freedom equal to do and a
cumulative probability equal to the critical
probability.

15.  The decision can be made by comparing the
calculated value and the tabulated value of the
test statistic used for the given hypothesis
problem.
 If calculated value lies in the acceptance region
then we accept.
 Calculated value ≤ tabulated value , H0 is
accepted.

17. Hypothesis testing is a process used to evaluate the
strength of
Evidence from sample and provides a framework for
making
Determinations related to the population.
Basically an idea that must be put to the test . A research
Questions should lead to clear, testable predictions.

18.  Procedure of setting null and alternative
hypothesis
( retrieved from ,
https://youtu.be/HTEW4L1iGoM)
Setting of level of significance and other
procedure (retrieved from,
https://youtu.be/h3U63-P--Y)