I would like some help with this SPSS assignment. I do not believe I am entering
ID: 3221327 • Letter: I
Question
I would like some help with this SPSS assignment. I do not believe I am entering the data correctly or perhaps I am missing a crucial detail. If anyone has SPSS could you please do this and post a picture of the printout/output that you get? I would greatly appreciate it.
Once you have entered the data run the following analyses. Data Editor Spreadsheet. Please note: Dataset. Enter the data below into yo 1) Calculate a One-Way Repeated Measures ANOVA Go under Analyze' then "General Linear Model" then Repeated Measures..." REPEATED MEASURES DEFNE FACTORS -Now a subjects column is needed! Label the columns "subjects", "hour1 "hour2", & "hour3" 'Number of Factor Name: type "hours" Levels: type "3" Click 147 REPEATED MEASURES' 14 Click to highlight then move "hour1", "hour2", & "hour3" to 36 48 "Within subjects variables (hours: 154 45 Click options 167 165 61 DISPLAY 151 150 150 Check 'Descriptive Statistic' & 170 63 "Estimates of Effect Size' 40 37 Click "ESTINMATE MARGINAL MEANS' 149 13 Display Means for: Check 'Compare Main Effects' pull-down to select 'Bonferroni' Click Continue ClickExplanation / Answer
GLM hour1 hour2 hour3
/WSFACTOR=hours 3 Polynomial
/METHOD=SSTYPE(3)
/PRINT=DESCRIPTIVE ETASQ
/CRITERIA=ALPHA(.05)
/WSDESIGN=hours.
General Linear Model
Within-Subjects Factors
Measure: MEASURE_1
hours
Dependent Variable
1
hour1
2
hour2
3
hour3
Descriptive Statistics
Mean
Std. Deviation
N
hour1
152.3077
11.36797
13
hour2
149.6923
12.01655
13
hour3
148.3077
10.54660
13
Multivariate Testsa
Effect
Value
F
Hypothesis df
Error df
Sig.
Partial Eta Squared
hours
Pillai's Trace
.350
2.968b
2.000
11.000
.093
.350
Wilks' Lambda
.650
2.968b
2.000
11.000
.093
.350
Hotelling's Trace
.540
2.968b
2.000
11.000
.093
.350
Roy's Largest Root
.540
2.968b
2.000
11.000
.093
.350
a. Design: Intercept
Within Subjects Design: hours
b. Exact statistic
Mauchly's Test of Sphericitya
Measure: MEASURE_1
Within Subjects Effect
Mauchly's W
Approx. Chi-Square
df
Sig.
Epsilonb
Greenhouse-Geisser
Huynh-Feldt
Lower-bound
hours
.526
7.070
2
.029
.678
.735
.500
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: hours
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
df
Mean Square
F
Sig.
Partial Eta Squared
hours
Sphericity Assumed
107.282
2
53.641
3.134
.062
.207
Greenhouse-Geisser
107.282
1.357
79.073
3.134
.086
.207
Huynh-Feldt
107.282
1.469
73.018
3.134
.081
.207
Lower-bound
107.282
1.000
107.282
3.134
.102
.207
Error(hours)
Sphericity Assumed
410.718
24
17.113
Greenhouse-Geisser
410.718
16.281
25.227
Huynh-Feldt
410.718
17.631
23.295
Lower-bound
410.718
12.000
34.226
Tests of Within-Subjects Contrasts
Measure: MEASURE_1
Source
hours
Type III Sum of Squares
df
Mean Square
F
Sig.
Partial Eta Squared
hours
Linear
104.000
1
104.000
4.856
.048
.288
Quadratic
3.282
1
3.282
.256
.622
.021
Error(hours)
Linear
257.000
12
21.417
Quadratic
153.718
12
12.810
Tests of Between-Subjects Effects
Measure: MEASURE_1
Transformed Variable: Average
Source
Type III Sum of Squares
df
Mean Square
F
Sig.
Partial Eta Squared
Intercept
878700.410
1
878700.410
2506.044
.000
.995
Error
4207.590
12
350.632
RMANOVA F=3.134, P=0.032 which is > 0.05 level.
Post hoc test not necessary
Within-Subjects Factors
Measure: MEASURE_1
hours
Dependent Variable
1
hour1
2
hour2
3
hour3