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  31MAR2017 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 nonmissing 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 Statistics^{a}  
N  Mean  
test1  40  96.68 
Valid N (listwise)  40 
a. gender = 0 
gender = 1
Descriptive Statistics^{a}  
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  31MAR2017 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  Userdefined 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 prespecified percent of outliers and other extreme values, the mean will be 100.67.
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