Bella Capelli Academy Statistics Questions Need attached statistics questions answered. Please ensure to label the work properly……………. Chi-Square

Bella Capelli Academy Statistics Questions Need attached statistics questions answered. Please ensure to label the work properly……………. Chi-Square Test for Independence
Question 1:
A researcher is interested in knowing if there are differences between the incidence of accidents
among experienced and inexperienced pilots. They were able to collect 62 responses from a
random number of pilots. Among them, 17 experienced pilots were in accidents, 26 were not; 13
inexperienced pilots were in accidents, 6 were not. Construct a contingency table. Run the Chi-
Square test for independence using the calculator in the Module.
State your findings and their significance. Do not forget to give summary statistics in APA
format
Question 2:
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 the calculator in
the module. Construct a contingency table.
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?
Sample Size and Power
Question 1:
You wish to conduct an ANOVA (one way/omnibus) in your ASCI 691 capstone project. In order
to insure 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, a = 0.05, and a
minimum power of 0.80. Your experiment utilizes three (3) groups. What is the required sample
size (a prion)? How many data points should exist in each group?
Question 2:
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 3:
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 4:
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?
Chi-Square Goodness of Fit Test
A researcher has four prototypes for a small Unmanned Aerial System controller and wants to
know which one that users prefer. The researcher asks 120 participants to use each controller
and annotate which one they liked best. At the conclusion of the study, the researcher hopes to
have a clearly identified prototype that is best preferred among the four. The table below
represents the number of times each prototype was chosen by the participants.
Prototype A
14
Prototype B
34
Prototype C
61
Prototype D
11
Use the five-step hypothesis testing process and StatCrunch to determine if there is a preferred
prototype.
Non-Parametrics
Question 1
Name three cases when you should use non-parametric analysis in place of parametric?
Question 2
What are some disadvantages of using non-parametric analysis (versus parametric)?
Question 3
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

Purchase answer to see full
attachment