I am glad that I first read the chapters from the text before I viewed the video. Personally, I found the textbook more helpful. But, all in all, the video did a fair job buttressing my 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 Coups, 2011, p. 145). I also learned that hypothesis testing follows a set procedure that appears as follows:

Step 1) Restate the question as a research hypothesis and a null hypothesis about the populations

- Basically, a researcher constructs a hypothesis. Then he/she forms a null hypothesis that opposes the research hypothesis in polar fashion. To help support one’s research hypothesis, one has to disprove the null hypothesis.

Step 2) Determine the characteristics of the comparison distribution

- When using two or more samples, one must gather information about the distribution of means.

Step 3) Determine the cutoff sample score on the comparison distribution at which the null hypothesis should be rejected

- Most researchers choose a significance level of 0.05 or 0.01.

Step 4) Determine your sample’s score on the comparison distribution

Step 5) Decide whether to reject the null hypothesis
(Retrieved from the textbook)

The textbook further introduced me to the notions of one and two-tailed tests, as well as Type I and Type II decision errors, which are highly essential in hypothesis testing.

From the Hypothesis Testing Video, I found out how hypothesis testing is...

...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...

...than 2100 square feet. Can we conclude that the mean size of homes sold in the Denver area is more than 2100 square feet? Use the .01 significance level. What is the p-value?
Answer to the question No.4
i. Hypothesistesting:
Step1: State the Null Hypothesis (H0) and Alternative Hypothesis (H1)
H0 : μ ≤ $ 2200 i.e.; mean selling price of homes in Denver is not more than $2200
H1 : μ > $ 2200 i.e.; mean selling price of...

...Business Statistics, 9e (Groebner/Shannon/Fry)
Chapter 10 Estimation and HypothesisTesting for Two Population Parameters
1) The Cranston Hardware Company is interested in estimating the difference in the mean purchase for men customers versus women customers. It wishes to estimate this difference using a 95 percent confidence level. If the sample size is n = 10 from each population, the samples are independent, and sample standard deviations are used, and...

...4 Hypothesistesting in the multiple regression model
Ezequiel Uriel
Universidad de Valencia
Version: 09-2013
4.1 Hypothesistesting: an overview
4.1.1 Formulation of the null hypothesis and the alternative hypothesis
4.1.2 Test statistic
4.1.3 Decision rule
4.2 Testing hypotheses using the t test
4.2.1 Test of a single parameter
4.2.2 Confidence intervals
4.2.3 Testing...

...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...

...HypothesisTesting 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...

...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...

...Hypothesistesting
Use of hypothesistesting can be very useful during decision-making connected with statistical data. A hypothesis is a statement made about a population parameter e.g. a mean and variance of a population. Hypothesistesting is a statistical process, which gives ideas or theories and then determine whether these ideas are true or false. The conclusions in...