Independent Samples Test

Students will use the document attached and answer the entire question in APA format. Please provide your answer directly underneath the question.
GG= Martian is Good. John is good
BG= Martian was bad. John is good.
GB= Martian is good, John is bad.
BB= Both are bad
1. Does John's sentence DEPEND on the experimental condition?
It's not significant because the ANOVA was greater than .05.
No, John's sentence does not depend on the condition (F = 1.188, P = 0.317). This is primarily because a Turkey Post hoc test revealed that the condition to determine the sentence was not statistically significant as it was greater than the p-value = 0.05 after taking BG and GB conditions compared to the GG. There was no significant difference between GB and BB.
Report

JohnToJail

GG=1, GB=2, BG=3, BB=4

Mean

N

Std. Deviation

1.00

7.8065

31

3.81593

2.00

6.5156

32

3.85312

3.00

8.3529

34

4.14058

4.00

7.1000

35

4.94648

Total

7.4470

132

4.24321

ANOVA

JohnToJail


Sum of Squares

df

Mean Square

F

Sig. (this is p)

Between Groups

63.883

3

MSB 21.294

1.188

.317

Within Groups

2294.746

128

MSW 17.928



Total

2358.629

131




There are no statistical differences. Therefore, John's sentence does not depend on the condition.
Multiple Comparisons

Dependent Variable: JohnToJail

Bonferroni

(I) GG, GB, BG, BB

(J) GG, GB, BG, BB

Mean Difference (I-J)

Std. Error

Sig.

95% Confidence Interval






Lower Bound

Upper Bound

1

2

1.29083

1.06703

1.000

-1.5687

4.1503


3

-.54649

1.05147

1.000

-3.3643

2.2713


4

.70645

1.04429

1.000

-2.0921

3.5050

2

1

-1.29083

1.06703

1.000

-4.1503

1.5687


3

-1.83732

1.04285

.483

-4.6320

.9574


4

-.58437

1.03560

1.000

-3.3597

2.1909

3

1

.54649

1.05147

1.000

-2.2713

3.3643


2

1.83732

1.04285

.483

-0.9574

4.6320


4

1.25294

1.01956

1.000

-1.4794

3.9852

4

1

-.70645

1.04429

1.000

-3.5050

2.0921


2

.58437

1.03560

1.000

-2.1909

3.3597


3

-1.25294

1.01956

1.000

-3.9852

1.4794

1 Does Gender impact how long John goes to jail?
Group Statistics


1=Female, 2=Male

N

Mean

Std. Deviation

Std. Error Mean

JohnToJail

1.00

85

7.8059

4.38619

.47575


2.00

47

6.7979

3.93377

.57380

Independent Samples Test


Levene's Test for Equality of Variances

t-test for Equality of Means


F

Sig.

t

df

Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference









Lower

Upper

JohnToJail

Equal variances assumed

.930

.337

1.310

130

0.192

1.00801

.76920

-.51375

2.52977


Equal variances not assumed



1.352

104.055

0.179

1.00801

074537

-.47009

2.48611

No, gender does not impact how long one will be jailed. This is primarily because the p-value of Levene's test is printed as 0.337, which is greater than the p-value = 0.05. Therefore, in this case, we approve the null of Levene's test and conclude the jail time for females is not significantly different than the males. Following this, it is evident that the researcher should look at the equal variances assumed row for the t-test and the corresponding confidence interval results.
3. Does Condition impact how we view John?
Report

1 Love, 5 Hate

GG=1, GB=2, BG=3, BB=4

Mean

N

Std. Deviation

1.00

3.2903

31

1.03902

2.00

3.0625

32

1.07576

3.00

4.4706

34

.70648

4.00

3.7143

35

1.10004

Total

3.6515

132

1.11878

ANOVA

1= Love, 5=Hate


Sum of Squares

df

Mean Square

F

Sig.

Between Groups

38.094

3

12.698

12.912

.000

Within Groups

125.876

128

.983



Total

163.970

131




1 2 3 4 = to gg gb bg & bb
Multiple Comparisons

Dependent Variable: 1= Love, 5=Hate

Bonferroni

(I) GG, GB, BG, BB

(J) GG, GB, BG, BB

Mean Difference (I-J)

Std. Error

Sig.

95% Confidence Interval






Lower Bound

Upper Bound

1

2

0.228

.250

1.000...