IBM SPSS

Descriptive Statistics

Descriptive Statistics
 NRangeMinimumMaximumMeanStd. DeviationVariance
StatisticStatisticStatisticStatisticStatisticStd. ErrorStatisticStatistic
Age58.0023.0031.0026.00001.516583.3911611.500
Weight540.00125.00165.00148.00006.4420514.40486207.500
Pretest_Score518.0065.0083.0073.60003.736318.3546469.800
Posttest_Score515.0075.0090.0082.00002.549515.7008832.500
Valid N (listwise)5       

Frequency Distribution

Statistics

Statistics
 AgeWeightGenderPretest_ScorePosttest_Score
NValid55555
Missing00000
Mean26.0000148.00001.400073.600082.0000
Std. Error of Mean1.516586.44205.244953.736312.54951
Median24.0000150.00001.000075.000080.0000
Mode24.00150.001.0065.0080.00
Std. Deviation3.3911614.40486.547728.354645.70088
Variance11.500207.500.30069.80032.500
Range8.0040.001.0018.0015.00
Minimum23.00125.001.0065.0075.00
Maximum31.00165.002.0083.0090.00

Frequency Table

Age
 FrequencyPercentValid PercentCumulative Percent
Valid23.00120.020.020.0
24.00240.040.060.0
28.00120.020.080.0
31.00120.020.0100.0
Total5100.0100.0 
Weight
 FrequencyPercentValid PercentCumulative Percent
Valid125.00120.020.020.0
150.00360.060.080.0
165.00120.020.0100.0
Total5100.0100.0 
Gender
 FrequencyPercentValid PercentCumulative Percent
ValidMale360.060.060.0
Female240.040.0100.0
Total5100.0100.0 
Pretest_Score
 FrequencyPercentValid PercentCumulative Percent
Valid65.00240.040.040.0
75.00120.020.060.0
80.00120.020.080.0
83.00120.020.0100.0
Total5100.0100.0 
Posttest_Score
 FrequencyPercentValid PercentCumulative Percent
Valid75.00120.020.020.0
80.00240.040.060.0
85.00120.020.080.0
90.00120.020.0100.0
Total5100.0100.0 

Post-test Score Graph

SPSS Assignment Table

If we think about each situation on its own, we can use a paired t-test (also called a dependent t-test) to see if there’s a big difference between the scores before and after. This test works well when the same people are tested twice in different situations (like before and after a test). With a significance level of 0.05, the t-test will show us if the average difference is really different from zero.

Paired-Samples T-test

Paired Samples Statistics
 MeanNStd. DeviationStd. Error Mean
Pair 1Posttest_Score82.000055.700882.54951
Pretest_Score73.600058.354643.73631
Paired Samples Correlations
 NCorrelationSig.
Pair 1Posttest_Score & Pretest_Score5.887.045
Paired Samples Test
 Paired DifferencestdfSig. (2-tailed)
MeanStd. DeviationStd. Error Mean95% Confidence Interval of the Difference
LowerUpper
Pair 1Posttest_Score – Pretest_Score8.400004.219001.886803.1614113.638594.4524.011
ItemResponseComment
1. What’s the mean?The mean difference between the pretest scores and post-test scores is 8.4.On average, the scores increased by 8.4 points between the pretest and post-test for all the cases. This means that overall, there was an improvement in scores from before to after the test.
2. What’s the t-test resultsThe t-test resulted in a t-value of 4.452 with 4 degrees of freedom.The t-value of 4.452 shows there’s a big difference between the scores before and after the test. At a significance level of 0.05, this t-value tells us it’s unlikely the score difference happened just by luck.
3. What’s the standard deviationThe standard deviation of the differences between the pretest scores and post-test scores is approximately 4.219.The standard deviation of 4.219 shows how much the scores before and after the test vary. A small standard deviation means the differences are pretty consistent or close to the average difference of 8.4.
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