(See attached file for full problem description with proper symbols and diagrams)

---
2. What is the critical F value for a sample of four observations in the numerator and seven in the
denominator? Use a one-tailed test and the .01 significance level.

3. The following hypotheses are given.

A random sample of eight observations from the first population resulted in a standard
deviation of 10. A random sample of six observations from the second population
resulted in a standard deviation of 7. At the .02 significance level, is there a difference
in the variation of the two populations?

4. The following hypotheses are given.

A random sample of five observations from the first population resulted in a standard
deviation of 12. A random sample of seven observations from the second population
showed a standard deviation of 7. At the .01 significance level, is there more variation
in the first population?

8. The following is sample information. Test the hypothesis at the .05 significance level that the
treatment means are equal.

a. State the null hypothesis and the alternate hypotheses.
b. What is the decision rule?
c. Compute SST, SSE, and SS total.
d. Complete an ANOVA table.
e. State your decision regarding the null hypothesis.

24. The following is a partial ANOVA table.

Complete the table and answer the following questions. Use the .05 significance level.
a. How many treatments are there?
b. What is the total sample size?
c. What is the critical value of F?
d. Write out the null and alternate hypotheses.
e. What is your conclusion regarding the null hypothesis?
---

Based on your experience using ANOVA and nonparametric tests, what additional information would you recommend to the key decision maker to solve the challenges given in a company that provides software solutions to wide range of clients?

Consider the different post hoc tests discussed in the readings and respond to the following:
Describe the general rationale behind using post hoc tests (i.e., when they are used and why).
One of the advantages of using an ANOVA (compared to using t-tests) is also a disadvantageâ€”using an ANOVA makes it necessary to use

Can you help me answer these questions
What is the theory underlying ANOVA? Why is it important? What are the differences between a two sample t-test and ANOVA hypothesis testing?
Why do we use nonparametric tests?
Describe a psychological research situation or scenario that would use a nonparametric test. Why would t

Is it a one-way, two-way, or repetitive problem?
3. A nurse educator desires to know if equivalent forms of a test produce equal results. The following data was collected on nurse ethics tests.
A B C D
78 71 73 81
84 69 61 77
65 77 79 88
89 82 68 91
72 85 67 90
55 88 77 83
68 70 72 85
73 79 83 87
71 91 80 93
76

Please see 2 files attached
STATS 2
Using the database provided (finalll.doc), calculate three different statistical tests chosen from the following:
1. Unpaired t-test
2. Paired t-test
3. One way ANOVA
4. Two - way ANOVA
If your database was constructed according to the directions, it should be appropriate for ap

The data file contains the individual data from 102 different participants. An equal number of participants (n=34) were tested in each of the three conditions (Method of Limits, Method of Constant Stimuli, and Method of Adjustment).
The task is to analyze the data to determine if there are any significant differences in eithe

A market researcher is interested in knowing the type of training that works best for DVD users. Thirty consumers are randomly selected from a population of known DVD owners (i.e., users). Ten users are trained by giving them the DVD user's manual and allowing them to read it. Another ten users are trained from a 30 minute DVD u

Can the formal hypothesis testing approach be used for nonparametric tests? How are parametric and nonparametric statistics different? How are parametric and nonparametric statistics similar?

The original concepts of analysis of variance came from the work of Sir Ronald A. Fisher, an English statistician. This technique, better known as ANOVA, has become one of the most commonly used research methods for testing differences among several population means. If only two populations are in question, ANOVA can be used; ho