76-15-3

GET

FILE=’ C:\psy7615\assess3\cf_unit_8.sav’.

DATASET NAME DataSet2 WINDOW=FRONT.

DATASET ACTIVATE DataSet2.

DATASET CLOSE DataSet1.

SORT CASES  BY gender.

SPLIT FILE SEPARATE BY gender.

DESCRIPTIVES VARIABLES=test1

/STATISTICS=MEAN.

 

 

 

Descriptives

 

 

Notes
Output Created 31-MAR-2017 17:31:11
Comments  
Input Data C:\psy7615\assess3\cf_unit_8.sav
Active Dataset DataSet2
Filter <none>
Weight <none>
Split File gender
N of Rows in Working Data File 80
Missing Value Handling Definition of Missing User defined missing values are treated as missing.
Cases Used All non-missing data are used.
Syntax DESCRIPTIVES VARIABLES=test1

/STATISTICS=MEAN.

Resources Processor Time 00:00:00.00
Elapsed Time 00:00:00.02

 

 

[DataSet2] C:\psy7615\assess3\cf_unit_8.sav

 

 

 

gender = 0

 

 

Descriptive Statisticsa
  N Mean
test1 40 96.68
Valid N (listwise) 40  

 

a. gender = 0

 

 

 

gender = 1

 

 

Descriptive Statisticsa
  N Mean
test1 40 100.43
Valid N (listwise) 40  

 

a. gender = 1

 

SPLIT FILE OFF.

EXAMINE VARIABLES=test1 BY gender

/PLOT NONE

/STATISTICS DESCRIPTIVES

/CINTERVAL 95

/MISSING LISTWISE

/NOTOTAL.

 

 

 

Explore

 

 

Notes
Output Created 31-MAR-2017 17:32:50
Comments  
Input Data C:\psy7615\assess3\cf_unit_8.sav
Active Dataset DataSet2
Filter <none>
Weight <none>
Split File <none>
N of Rows in Working Data File 80
Missing Value Handling Definition of Missing User-defined missing values for dependent variables are treated as missing.
Cases Used Statistics are based on cases with no missing values for any dependent variable or factor used.
Syntax EXAMINE VARIABLES=test1 BY gender

/PLOT NONE

/STATISTICS DESCRIPTIVES

/CINTERVAL 95

/MISSING LISTWISE

/NOTOTAL.

Resources Processor Time 00:00:00.02
Elapsed Time 00:00:00.03

 

 

[DataSet2] C:\psy7615\assess3\cf_unit_8.sav

 

 

 

gender

 

 

Case Processing Summary
  gender Cases
Valid Missing Total
N Percent N Percent N Percent
test1 0 40 100.0% 0 0.0% 40 100.0%
1 40 100.0% 0 0.0% 40 100.0%

 

 

Descriptives
  gender Statistic Std. Error
test1 0 Mean 96.68 2.428
95% Confidence Interval for Mean Lower Bound 91.76  
Upper Bound 101.59  
5% Trimmed Mean 96.56  
Median 95.00  
Variance 235.763  
Std. Deviation 15.355  
Minimum 69  
Maximum 126  
Range 57  
Interquartile Range 24  
Skewness .160 .374
Kurtosis -.758 .733
1 Mean 100.43 2.505
95% Confidence Interval for Mean Lower Bound 95.36  
Upper Bound 105.49  
5% Trimmed Mean 100.67  
Median 101.00  
Variance 250.969  
Std. Deviation 15.842  
Minimum 64  
Maximum 135  
Range 71  
Interquartile Range 21  
Skewness -.282 .374
Kurtosis .050 .733

 

Split file descriptive statistics

The dataset was split by gender and its descriptives obtained. According to the output, it’s clear that the mean test1 score for each gender was 96.68 and 100.43 of 40 valid cases for female and male genders respectively. We’ll need to carry out further hypothesis tests to determine whether the obtained test1 means for each gender is statistically significant or not. It’s possible to carry out such test within SPSS. However, in this case, the descriptive statistic obtained, the mean of test1, informs us that gender 0, female, had a smaller mean than gender 1, male. It helps us to visualize the meaning and patterns observed in our sample data.

After analyzing the split file, the split was turned off, and the descriptives for test1 were obtained. The output indicates the mean as 96.68 with a standard deviation of 2.428. At the 95% confidence interval for mean, we have it that the mean ranges from 91.76 to 101.59. What this communicates is that the mean for each gender, 0 and 1, lies within the lower and upper bound of the mean when the data set isn’t split. Further, from the SPSS output of the explore command when the split is turned off informs us that the 5% trimmed mean is 100.67. While additional inferential statistical operations are necessary to understand the meaning of these values, the 5% trimmed mean informs us that after removing a pre-specified percent of outliers and other extreme values, the mean will be 100.67.

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