Question

Dr. Griswald wants to see how cell phone use impacts reaction time. To test this, Dr. Griswald conducted a study where participants are randomly assigned to one of two conditions while driving: a cell phone or no cell phone. Participants were then instructed to complete a driving simulator course where reaction times (in milliseconds) were recorded by how quickly they hit the breaks in response to a cat running in the middle of the road during the course. Below are the data. What can Dr. Griswald conclude with an an α of 0.05?

cell phone	no cell phone
235 241 240 243 232	232 238 227 228 227

a) What is the appropriate test statistic?
---Select--- na z-test One-Sample t-test Independent-Samples t-test Related-Samples t-test
Then state conditions,
Condition 1:
---Select--- cell phone simulator course reaction time dog running no cell phone
Condition 2:
---Select--- cell phone simulator course reaction time dog running no cell phone

b) Compute the appropriate test statistic(s) to make a decision about H₀.
(Hint: Make sure to write down the null and alternative hypotheses to help solve the problem.)
critical value =  ; test statistic =  
Decision:  ---Select--- Reject H0 Fail to reject H0

c) If appropriate, compute the CI. If not appropriate, input "na" for both spaces below.
[  ,  ]

d) Compute the corresponding effect size(s) and indicate magnitude(s).
If not appropriate, input and/or select "na" below.
d =  ;  ---Select--- na trivial effect small effect medium effect large effect
r² =  ;  ---Select--- na trivial effect small effect medium effect large effect
Make an interpretation based on the results.

A.Cell phone use results in significantly slower reaction time than no cell phone use.

B. No cell phone results in significantly slower reaction time than cell phone use.   

C. There is no significant reaction time difference between cell phone use or no cell phone use.

Answer 1

a) What is the appropriate test statistic?

Independent-Samples t-test

b)

Two-Sample T-Test and CI: cell phone, no cell phone

Method

μ₁: mean of cell phone

µ₂: mean of no cell phone

Difference: μ₁ - µ₂

Equal variances are assumed for this analysis.

Descriptive Statistics

Sample	N	Mean	StDev	SE Mean
cell phone	5	238.20	4.55	2.0
no cell phone	5	230.40	4.72	2.1

Estimation for Difference

Difference	Pooled StDev	95% CI for Difference
7.80	4.64	(1.04, 14.56)

Test

Null hypothesis	H₀: μ₁ - µ₂ = 0
Alternative hypothesis	H₁: μ₁ - µ₂ ≠ 0

Test statistic	DF	P-Value
2.66	8	0.029

critical value t_0.025,8 = 2.306

since test statistic is greater than critical value we reject null hypothesis.

c) 95% CI

(1.04, 14.56)

d)

Cohen's d = (230.4 - 238.2) ⁄ 4.64= 1.68. large effect

r² = 0.415 , large effect

Make an interpretation based on the results.

No cell phone results in significantly slower reaction time than cell phone use.