Can someone please USE SPSS and show me their analysis? A behavior analyst would
ID: 2908582 • Letter: C
Question
Can someone please USE SPSS and show me their analysis?
A behavior analyst would like to evaluate the effectiveness of a new technique for controlling classroom outbursts of unruly children. For a sample of n=4 children the number of outbursts is recorded 1 day before treatment and again 1 week, 1 month and 6 months after treatment. The data are as follows:
Child --Before-- 1 week --1 month-- 6 months
A --8 --2-- 1-- 1
B-- 4 --1 --1 --0
C--6-- 2-- 0-- 2
D-- 8-- 3 --4 --1
Use a repeated measures ANOVA with alpha = .05 to determine whether there are significant changes in behavior over time (write all the steps involved in testing the hypothesis). Use SPSS to solve this problem. Please make sure to show all the steps of hypothesis testing.
Explanation / Answer
Result:
Can someone please USE SPSS and show me their analysis?
A behavior analyst would like to evaluate the effectiveness of a new technique for controlling classroom outbursts of unruly children. For a sample of n=4 children the number of outbursts is recorded 1 day before treatment and again 1 week, 1 month and 6 months after treatment. The data are as follows:
Child --Before-- 1 week --1 month-- 6 months
A --8 --2-- 1-- 1
B-- 4 --1 --1 --0
C--6-- 2-- 0-- 2
D-- 8-- 3 --4 --1
Use a repeated measures ANOVA with alpha = .05 to determine whether there are significant changes in behavior over time (write all the steps involved in testing the hypothesis). Use SPSS to solve this problem. Please make sure to show all the steps of hypothesis testing.
Ho: There is no changes in behavior over time
H1: There is a changes in behavior over time
Calculated F= 21.000, P=0.000 which is less than 0.05 level. Ho is rejected.
We conclude that there is significant changes in behavior over time.
Enter the data in 4 columns
v1
v2
v3
v4
8
2
1
1
4
1
1
0
6
2
0
2
8
3
4
1
In menu select Analyze, General Linear Model, Repeated Measures enter number of levels as 4 and define the 4 variables as 4 factors.
OR
Spss syntax
GLM v1 v2 v3 v4
/WSFACTOR=factor1 4 Polynomial
/METHOD=SSTYPE(3)
/PRINT=DESCRIPTIVE
/CRITERIA=ALPHA(.05)
/WSDESIGN=factor1.
Spss output:
General Linear Model
[DataSet0]
Within-Subjects Factors
Measure: MEASURE_1
factor1
Dependent Variable
1
v1
2
v2
3
v3
4
v4
Descriptive Statistics
Mean
Std. Deviation
N
v1
6.5000
1.91485
4
v2
2.0000
.81650
4
v3
1.5000
1.73205
4
v4
1.0000
.81650
4
Multivariate Tests
Effect
Value
F
Hypothesis df
Error df
Sig.
factor1
Pillai's Trace
.948
18.062
2.000
2.000
.052
Wilks' Lambda
.052
18.062
2.000
2.000
.052
Hotelling's Trace
18.062
18.062
2.000
2.000
.052
Roy's Largest Root
18.062
18.062
2.000
2.000
.052
Mauchly's Test of Sphericity
Measure: MEASURE_1
Within Subjects Effect
Mauchly's W
Approx. Chi-Square
df
Sig.
Epsilon
Greenhouse-Geisser
Huynh-Feldt
Lower-bound
factor1
.000
.
5
.
.640
1.000
.333
Tests of Within-Subjects Effects
Measure: MEASURE_1
Source
Type III Sum of Squares
df
Mean Square
F
Sig.
factor1
Sphericity Assumed
77.000
3
25.667
21.000
.000
Greenhouse-Geisser
77.000
1.921
40.091
21.000
.002
Huynh-Feldt
77.000
3.000
25.667
21.000
.000
Lower-bound
77.000
1.000
77.000
21.000
.020
Error(factor1)
Sphericity Assumed
11.000
9
1.222
Greenhouse-Geisser
11.000
5.762
1.909
Huynh-Feldt
11.000
9.000
1.222
Lower-bound
11.000
3.000
3.667
Tests of Within-Subjects Contrasts
Measure: MEASURE_1
Source
factor1
Type III Sum of Squares
df
Mean Square
F
Sig.
factor1
Linear
57.800
1
57.800
51.000
.006
Quadratic
16.000
1
16.000
12.000
.041
Cubic
3.200
1
3.200
2.667
.201
Error(factor1)
Linear
3.400
3
1.133
Quadratic
4.000
3
1.333
Cubic
3.600
3
1.200
Tests of Between-Subjects Effects
Measure: MEASURE_1
Transformed Variable: Average
Source
Type III Sum of Squares
df
Mean Square
F
Sig.
Intercept
121.000
1
121.000
27.923
.013
Error
13.000
3
4.333
v1
v2
v3
v4
8
2
1
1
4
1
1
0
6
2
0
2
8
3
4
1