DESCRIPTIVE STATISTICS CASE STUDY

DESCRIPTIVE STATISTICS CASE STUDY: The four variables shown in the data set below are set up to represent a fictitious study of gender, weight and fitness score. The variables include gender, ranking, weight and score. In this example, gender is coded as m or f (recoded as 1 or 2 for computations), weight is the participant's weight, score is a value that the participant scored in a fitness test and rank is their ranking based on that score. Gender Ranking Weight Score m 1 200 95 m 2 110 92 f 3 103 91 f 4 145 90 f 5 130 88 m 6 180 82 m 7 170 80 f 8 90 75 f 9 102 70 m 10 225 60 m 11 225 59 m 12 108 55 f 13 108 55 m 14 108 55 m 15 167 50 EACH OF THE VARIABLES IS EXAMINED IN THE CHART BELOW: Statistics GENDER RANKING SCORE WEIGHT N Valid Missing Statistic Statistic 15 0 15 0 15 0 15 0 Mean Statistic St. Error 1.40 .13 8.0000 1.1547 73.1333 4.1928 144.7333 12.0224 Median Statistic 1.00 8.0000 75.0000 130.0000 Mode Statistic 1 1.00 a 55.00 108.00 Std. Deviation Statistic .51 4.4721 16.2387 46.5625 Variance Statistic .26 20.0000 263.6952 2168.0667 Skewness Statistic St. Error .455 .580 .000 .580 -.065 .580 .625 .580 Kurtosis Statistic St. Error -2.094 1.121 -1.200 1.121 -1.753 1.121 -1.037 1.121 Range Statistic 1 14.00 45.00 135.00 Minimum Statistic 1 1.00 50.00 90.00 Maximum Statistic 2 15.00 95.00 225.00 a. Multiple modes exist. The smallest value is shown =============================================================== YOUR TURN Using the values from the GENDER variable in table above, answer the following questions. =============================================================== 1. What type of data does gender represent? 2. What does the mean gender of 1.40 tell us? 3. What would be the appropriate measure of central tendency for GENDER? 4. What is the value for central tendency? =============================================================== YOUR TURN Using the values from the RANKING variable in table above, answer the following questions.