Three teaching methods were tested on a group of 19 students with homogeneous backgrounds in statistics and comparable aptitudes. Each student was randomly assigned to a method and at the end of a 6-week program was given a standardized exam. Because of classroom space and group size, the students were not equally allocated to each method. The results are shown in the table below. Test for a difference in distributions (medians) of the test scores for the different teaching methods using the Kruskal-Wallis test. Method 1 94 87 90 74 86 97 Method 2 82 85 79 84 61 72 80 Method 3 89 68 72 76 69 65 1. Enter the time values into one variable and the corresponding teaching method number (1 for Method 1, 2 for Method 2, 3 for Method 3) into another variable (see figure, below). Be sure to code your variables appropriately.

2.

Select Graphs Boxplot… (Simple, Summaries for groups of cases) with the variable measured (Test Score) and the category axis variable (Teaching Method) entered (see figures, below). Click “OK”.

3.

Your resulting side-by-side boxplots will appear (see figure, below). As long as the boxes have approximately the same shape, you may continue with the ANOVA procedure.

4.

Select Analyze

Nonparametric Tests

K Independent Samples… (see figure, below).

5.

Select “Test Score” as the test variable, select “Teaching Method” as the grouping factor, and click “Define Range…”. Enter the minimum value (1) and the maximum value (3). Click “Continue” to close the range definitions and then click “OK”. (See the 3 figures, below.)

6.

Your output should look like this.

7.

You should use the output information in the following manner to answer the question. Step 0 : Check Assumptions The samples were taken randomly and independently of each other. The populations have approximately the same shapes (according to the boxplots). All sample sizes are at least 6 if k = 3 (smallest is 6)....

...HypothesisTesting For a Population Mean
The Idea of HypothesisTesting
Suppose we want to show that only children have an average higher cholesterol level than the national average. It is known that the mean cholesterol level for all Americans is 190. Construct the relevant hypothesis test:
H0: = 190
H1: > 190
We test 100 only children and find that
x = 198
and suppose we...

...above information, what kind of hypothesis test will you conduct? The y-test, z-test, t-test, χ2-test, F-test, G-test, or even the y-not-test? Please explain.
4. (2 points) What will be the null hypothesis, the alternative hypothesis, and, hence, the "tailedness" of the test (left-tailed, right-tailed, or two-tailed)?
5. (10 points) What is be the corresponding test statistics?
6. (8 points) What is the corresponding p-value of...

...Lesson note #
Statistical Inference
Testing of Hypothesis
Type I Error:
Rejection of the null hypothesis when it is true is called a type I error.
Type II Error:
Acceptance of the null hypothesis when it is false is called a type II error.
|Decision of the test for the Null Hypothesis |The Null Hypothesis is |
|...

...Simple Hypothesis: A statisticalhypothesis which specifies the population completely (i.e. the form of probability distribution and all parameters are known) is called a simple hypothesis.
1. Composite Hypothesis: A statisticalhypothesis which does not specify the population completely (i.e. either the form of probability distribution or some parameters remain unknown) is called a Composite...

...CHAPTER 4 – THE BASIS OF STATISTICALTESTING
* samples and populations
* population – everyone in a specified target group rather than a specific region
* sample – a selection of individuals from the population
* sampling
* simple random sampling – identify all the people in the target population and then randomly select the number that you need for your research
* extremely difficult, time-consuming, expensive...

...five steps of hypothesistesting and the 5% significance level (i.e. alpha = .05), does showing the film change students’ attitudes towards the chronically mentally ill?
What does it mean to set alpha at .05?
Alpha means making a Type I error same as significance level. When the alpha is at .05 it means that the researcher doesn’t want to take a big risk therefore sets the alpha to .05. By doing this it will make it hard for hypothesis...

...Chapter 4. Hypothesistesting
The main aim of the module is to familiarize students with the theoretical knowledge of hypothesistesting and then train them in applying theory to economic practice.
After completing this module, students will be familiar with:
the procedure of hypothesistesting;
the possible outcomes in hypothesistesting;
the difference between...

...steps of hypothesistesting and the 5% significance level (i.e. alpha = .05), does showing the film change students’ attitudes towards the chronically mentally ill?
•
What does it mean to set alpha at .05? Alpha at .05 means there is a .05 probability or 5% chance of committing a Type I error, which means that we have rejected our null hypothesis and found support for our alternate hypothesis when, in fact, the null...

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