A hypothesis is a claim
Population mean
The mean monthly cell phone bill in this city is μ = $42
Population proportion
Example: The proportion of adults in this city with cell phones is π = 0.68 States the claim or assertion to be tested
Is always about a population parameter, not about a sample statistic

Is the opposite of the null hypothesis
e.g., The average diameter of a manufactured bolt is not equal to 30mm ( H1: μ ≠ 30 ) Challenges the status quo
Alternative never contains the “=”sign
May or may not be proven
Is generally the hypothesis that the researcher is trying to prove

Is the opposite of the null hypothesis
e.g., The average diameter of a manufactured bolt is not equal to 30mm ( H1: μ ≠ 30 ) Challenges the status quo
Alternative never contains the “=”sign
May or may not be proven
Is generally the hypothesis that the researcher is trying to prove

Is the opposite of the null hypothesis
e.g., The average diameter of a manufactured bolt is not equal to 30mm ( H1: μ ≠ 30 ) Challenges the status quo
Alternative never contains the “=”sign
May or may not be proven
Is generally the hypothesis that the researcher is trying to prove

If the sample mean is close to the stated population mean, the null hypothesis is not rejected.

If the sample mean is far from the stated population mean, the null hypothesis is rejected.

How far is “far enough” to reject H0?

The critical value of a test statistic creates a “line in the sand” for decision making -- it answers the question of how far is far enough.

Type I Error
Reject a true null hypothesis
Considered a serious type of error
The probability of a Type I Error is
Called level of significance of the test
Set by researcher in advance
Type II Error
Failure to reject a false null hypothesis
The probability of a Type II Error is β

Type I and Type II errors cannot happen at
the same time
A Type I error can only occur if H0 is true
A Type II error can only...

...Chapter-11
Testing of Hypothesis:
(Non-parametric Tests)
Chapter-11: Testing of Hypothesis - (Non-parametric Tests)
2
11.1. Chi - square ( χ )Test / Distribution
2
11.1.1. Meaning of Chi - square ( χ )Test
2
11.1.2. Characteristics of Chi - square ( χ )Test
2
11.2. Types of Chi - square ( χ )Test / Distribution
2
11.2.1. Chi - square ( χ )Test for Population Variance
2
11.2.2. Chi - square ( χ )Test for Goodness-of-Fit
2
11.2.3. Chi -...

...On
Hypothesis Testing
Submitted By: 090430 Date of Submission: 19.09.2010
Urban and Rural Planning Discipline
Khulna University, Khulna
Preface:
A hypothesis is a statement about a population parameter developed for the purpose of testing. The terms hypothesis testing and testing a hypothesis are used interchangeably. Hypothesis testing starts with a statement, or assumption,...

...
The word ‘Hypothesis is derived from a Greek word, which means ‘to suppose’. It is usually considered as the principal instrument in research. For a researcher it is a formal question that he or she intends to resolve. In this way a hypothesis may be defined as a proposition or a supposition. The main function of hypothesis is to guide the collection and processing of materials and direct the research....

...Hypothesis Testing I
Pat Obi
What is a “Hypothesis?”
A statement or claim about the value of a
population parameter: μ, σ2, p
Pat Obi, Purdue University Calumet
2
Decision Rule
1.
x 0
Z
s
n
Compare calculated Z value to Z value from
Table (critical Z value)
Reject H0 if calculated Z value lies in the
rejection/significance region (i.e. region)
ALTERNATIVELY:
2.
Compare p-value to
Reject H0 if p-value <
Pat Obi, Purdue...

...understanding of hypothesis testing. The textbook explained the aspects and steps of hypothesis testing in a legible fashion, while the video helped demonstrate a real-life application.
I learned from the text that hypothesis testing is a “Procedure for deciding whether the outcome of a study (results from a sample) supports a particular theory or practical innovation (which is thought to apply to a population)” (Aron A., Aron, E., and...

...RESEARCH METHODOLOGY
LESSON 20: PRINCIPLE OF HYPOTHESIS TESTING
So far we have talked about estimating a confidence interval along with the probability (the confidence level) that the true population statistic lies within this interval under repeated sampling. We now examine the principles of statistical inference to hypotheses testing. By the end of this chapter you should be able to
• Understand what is hypothesis testing • Examine issues relating to the...

...APP6JMaloney problems 2. 4, 6, 10, 18, 22, 24
2 ) The value of the z score un a hypothesis test is influenced by a variety of factors.
Assuming that all the other variables are held constant, explain how the value
of Z is influenced by each of the following?
Z= M - u / SD
a) Increasing the difference between the sample mean and the original.
The z score represents the distance of each X or score from the mean.
If the distance between the sample mean and the...

...“Accept” the Null Hypothesis
by Keith M. Bower, M.S. and James A. Colton, M.S.
Reprinted with permission from the American Society for Quality
When performing statistical hypothesis tests such as a one-sample t-test or the AndersonDarling test for normality, an investigator will either reject or fail to reject the null
hypothesis, based upon sampled data. Frequently, results in Six Sigma projects contain
the verbiage “accept the null...

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