In a longitudinal study of attitude toward statistics a doct

In a longitudinal study of attitude toward statistics, a doctoral student surveyed 10 doctoral
students at four times during their program: (a) before taking any statistics courses; (b) after
having taken one course; (c) after all required statistics courses; and (d) one semester after
completing their preliminary examination. In each instance, alternate forms of the Attitude
Towards Statistics instrument were used. The data were:

1. Analyze the data using an alpha of .05 in SPSS (Free trial of SPSS here: http://www-01.ibm.com/software/analytics/spss/products/statistics/downloads.html)
2. Writing the result in APA format.

SPSS out put

GLM v1 v2 v3 v4

/WSFACTOR=factor1 4 Polynomial

/METHOD=SSTYPE(3)

/EMMEANS=TABLES(factor1) COMPARE ADJ(BONFERRONI)

/PRINT=DESCRIPTIVE

/CRITERIA=ALPHA(.05)

/WSDESIGN=factor1.

Descriptive Statistics

Mean

Std. Deviation

40.50

11.008

42.40

11.806

43.00

11.126

36.80

10.390

Multivariate Tests^a

Effect

Value

Hypothesis df

Error df

Sig.

factor1

Pillai\'s Trace

.768

7.725^b

3.000

7.000

.013

Wilks\' Lambda

.232

7.725^b

3.000

7.000

.013

Hotelling\'s Trace

3.311

7.725^b

3.000

7.000

.013

Roy\'s Largest Root

3.311

7.725^b

3.000

7.000

.013

a. Design: Intercept

Within Subjects Design: factor1

b. Exact statistic

Mauchly\'s Test of Sphericity^a

Measure: MEASURE_1

Within Subjects Effect

Mauchly\'s W

Approx. Chi-Square

Sig.

Epsilon^b

Greenhouse-Geisser

Huynh-Feldt

Lower-bound

factor1

.509

5.209

.394

.688

.896

.333

Tests the null hypothesis that the error covariance matrix of the orthonormalized transformed dependent variables is proportional to an identity matrix.

a. Design: Intercept

Within Subjects Design: factor1

b. May be used to adjust the degrees of freedom for the averaged tests of significance. Corrected tests are displayed in the Tests of Within-Subjects Effects table.

Tests of Within-Subjects Effects

Measure: MEASURE_1

Source

Type III Sum of Squares

Mean Square

Sig.

factor1

Sphericity Assumed

234.275

78.092

15.916

.000

Greenhouse-Geisser

234.275

2.064

113.520

15.916

.000

Huynh-Feldt

234.275

2.687

87.190

15.916

.000

Lower-bound

234.275

1.000

234.275

15.916

.003

Error(factor1)

Sphericity Assumed

132.475

4.906

Greenhouse-Geisser

132.475

18.574

7.132

Huynh-Feldt

132.475

24.182

5.478

Lower-bound

132.475

9.000

14.719

Tests of Within-Subjects Contrasts

Measure: MEASURE_1

Source

factor1

Type III Sum of Squares

Mean Square

Sig.

factor1

Linear

55.125

20.066

.002

Quadratic

164.025

18.401

.002

Cubic

15.125

4.946

.053

Error(factor1)

Linear

24.725

2.747

Quadratic

80.225

8.914

Cubic

27.525

3.058

Tests of Between-Subjects Effects

Measure: MEASURE_1

Transformed Variable: Average

Source

Type III Sum of Squares

Mean Square

Sig.

Intercept

66178.225

138.576

.000

Error

4298.025

477.558

Estimated Marginal Means

factor1

Estimates

Measure: MEASURE_1

factor1

Mean

Std. Error

95% Confidence Interval

Lower Bound

Upper Bound

40.500

3.481

32.626

48.374

42.400

3.733

33.955

50.845

43.000

3.518

35.041

50.959

36.800

3.286

29.367

44.233

Pairwise Comparisons

Measure: MEASURE_1

(I) factor1

(J) factor1

Mean Difference (I-J)

Std. Error

Sig.^b

95% Confidence Interval for Difference^b

Lower Bound

Upper Bound

-1.900

1.016

.566

-5.318

1.518

-2.500

.885

.119

-5.478

.478

3.700^*

.790

.007

1.044

6.356

1.900

1.016

.566

-1.518

5.318

-.600

.733

1.000

-3.067

1.867

5.600^*

1.213

.008

1.520

9.680

2.500

.885

.119

-.478

5.478

.600

.733

1.000

-1.867

3.067

6.200^*

1.200

.004

2.163

10.237

-3.700^*

.790

.007

-6.356

-1.044

-5.600^*

1.213

.008

-9.680

-1.520

-6.200^*

1.200

.004

-10.237

-2.163

Based on estimated marginal means

*. The mean difference is significant at the .05 level.

b. Adjustment for multiple comparisons: Bonferroni.

Multivariate Tests

Value

Hypothesis df

Error df

Sig.

Pillai\'s trace

.768

7.725^a

3.000

7.000

.013

Wilks\' lambda

.232

7.725^a

3.000

7.000

.013

Hotelling\'s trace

3.311

7.725^a

3.000

7.000

.013

Roy\'s largest root

3.311

7.725^a

3.000

7.000

.013

Each F tests the multivariate effect of factor1. These tests are based on the linearly independent pairwise comparisons among the estimated marginal means.

a. Exact statistic

Report

A one-way within subjects (or repeated measures) ANOVA was conducted to compare the attitude towards statistics. There was a significant effect of the course, Wilks