Reference no: EM132657204 , Length: 2103 Words

Question 1.

As?ftw?re developer is interested in finding what the best color theme should be for an engine diagnostic program for the flight line. He is considering three different color themes (red, green, or blue). To determine which is preferred b? his users he invited 60 participants to view the three different designs (colors). He then asked them which one they liked best. The table below presents the number of times each design was chosen by the participants.

Red Green Blue
14 18 28

(a) Use appropriate words and statistics to describe the statistical results. Based on this data which design should he use? (Hint: Use StatCrunch STAT>Goodness-of-fit>Chi square test).

Question 2.

What foods do aeronautical engineers like?
There were three types of food, and the researcher recorded which foods were bought.

Peanut Butter Banana Hamburger
15 7 4

(a) Use appropriate words and statistics to describe the statistical results. Based on this data which food seems to be prefered?

Question 3.
A researcher is interested in knowing if there are differences between the incidence of accidents among pilots of different experience levels. They were able to collect 62 responses from a random number of pilots. Among them, 17 new pilots were in accidents, 26 were not;? 13 experienced pilots were in accidents, 6 were not.

• Construct a contingency table.
• Run the Chi-¬Square test for independence using StatCrunch.
• To access, click STAT>Tables>Contingency>With summary
• State your findings and their significance. Do not forget to give summary statistics in APA format.

Question 4.
A researcher has found that pilots taking an over the counter antihistamine have poor reaction times. They performed an experiment on 22 pilots: 11 took the medication and 11 did not. Their reaction times to a command by Air Traffic Control was considered to be adequate or inadequate. Among those taking the medication, 8 were rated inadequate and 3 adequate. Among those not-¬taking the medication, 10 were rated adequate and only 1 inadequate.

• Construct a contingency table.
• Run the Chi-¬Square test for independence using StatCrunch.
• To access, click STAT>Tables>Contingency>With summary
• State your findings and their significance. Do not forget to give summary statistics in APA format.
• What is the problem with this research study? Is the Chi-¬Square test appropriate? Why or why not? What could the researcher do to potentially rectify the problem?

Question 5.

Use a bag of M&MTM candies and perform a Chi-squared analysis. State a hypothesis and comment on how your results may differ from your peers in this course.

Remember to provide feedback to at least two of your classmates. Provide a constructive critique by answering these questions: Do you agree with their approach to the question asked? Why or why not? What new insight did you get from your classmates' response?

Question 6.

Name three cases when you should use non-parametric analysis in place of parametric?

Question 7.
What are some disadvantages of using non-parametric analysis (versus parametric)?

Question 8.
Match the non-parametric version of analysis with its parametric equivalent.
A. Mann-Whitney U 1. One-way ANOVA
B. Kruskal-Wallis 2. Paired sample t-test
C. Wilcoxon Signed Rank 3. Independent sample t-test
D. Friedman 4. Pearson correlation
E. Spearman's Rank 5. Repeated measure ANOVA

Question 9.
You wish to conduct an ANOVA (one way/omnibus) in your ASCI 691 capstone project. In order to ensure you have enough power to detect differences in your sample, you need to run a power analysis in G*Power. Assume that you are expecting a medium effect size, ? = 0.05, and a power of 0.80. Your experiment utilizes three (3) groups. What is the required sample size (a priori)? How many data points should exist in each group?

Question 10.
You conducted a Chi-Square Goodness of Fit Test in your ASCI 691 capstone project. Unfortunately, you did not get the sample size you had hoped for during your research. You were able to get 55 in the sample. Calculate your actual power (post hoc). You did a 2 X 2 table. Assume you had a medium effect size.

Question 11.
You conducted a t-test in your 691 capstone research. You found a statistically significant difference between your groups even though your sample size was relatively small. Upon conducting a post hoc power analysis you found that your actual power was 0.65. What should you do? Is there a problem with having a power less than 0.80 when you have significant differences?

Question 12.
You conducted a t-test in your 691 capstone research. You did not find a statistically significant difference between your groups even though your sample size was relatively small. Upon conducting a post hoc power analysis you found that your actual power was 0.57. What should you do? Is there a problem with having a power less than 0.80 when you do not have significant differences?