1. Use all the variables in the dataset
2. Create a correlation matrix of all the variables
3. Which pairs are correlated?
4. Run factor Analysis using all the variables
5. Obtain the scree plot & the Eigenvalue
6. Based on the scree plot, how many factors are optimal?
7. Under the model launch test the number of factors that is optimal
   1. Type 1 in the number of factors. Leave all the default settings, Select go. Report the estimates for the significant test. Is one factor sufficient?
   2. Repeat this step- click the arrow next to the Model Launch and type two in the number of factors box. Based on the significance test, are two factors sufficient?
8. If so, what at the variables loading on Factor 1 and Factor 2?
9. What do you think these variables describe?
10. Using your correlation matrix, describe the correlation between the variables loading for each factor.
11. Which variable is the least important in explaining the variance and factors in this dataset?
    

X Exercise - JMP Pro File Edit Tables Rows Cols DOE Analyze Graph Tools View Window Help Exercise weight waist pulse Notes Linnerud's fitness (Ibs) (in) (BPM) chins situps jumps Fit Model 191 36 50 16 60 189 37 52 2 110 60 93 38 58 12 107 101 162 35 62 12 105 37 G UI A W N 189 35 46 13 155 58 182 36 56 4 101 42 7 211 38 56 8 101 38 8 167 34 60 6 125 40 9 176 31 74 15 200 40 10 154 56 17 251 250 Columns (6/0) 11 50 17 120 38 weight * waist >K 12 52 13 210 115 215 pulse >k 13 64 14 105 chins 14 247 50 50 50 situps 15 46 70 w jumps 16 202 62 12 210 120 17 76 54 4 50 25 52 11 230 80 19 156 54 15 225 73 N 20 138 68 110 43 Rows All rows Selected Excluded oooo Hidden Labelled 12:53 AM 63.F Clear ~ 6 0 (4) Type here to search O " 10/15/2021