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Statitistics

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Statistics | AGE. What is your age? | N | Valid | 3006 | | Missing | 0 |

AGE. What is your age? | | Frequency | Percent | Valid Percent | Cumulative Percent | Valid | 18 | 68 | 2.3 | 2.3 | 2.3 | | 19 | 49 | 1.6 | 1.6 | 3.9 | | 20 | 52 | 1.7 | 1.7 | 5.6 | | 21 | 30 | 1.0 | 1.0 | 6.6 | | 22 | 38 | 1.3 | 1.3 | 7.9 | | 23 | 38 | 1.3 | 1.3 | 9.1 | | 24 | 39 | 1.3 | 1.3 | 10.4 | | 25 | 38 | 1.3 | 1.3 | 11.7 | | 26 | 39 | 1.3 | 1.3 | 13.0 | | 27 | 40 | 1.3 | 1.3 | 14.3 | | 28 | 37 | 1.2 | 1.2 | 15.6 | | 29 | 39 | 1.3 | 1.3 | 16.9 | | 30 | 41 | 1.4 | 1.4 | 18.2 | | 31 | 41 | 1.4 | 1.4 | 19.6 | | 32 | 38 | 1.3 | 1.3 | 20.9 | | 33 | 36 | 1.2 | 1.2 | 22.1 | | 34 | 19 | .6 | .6 | 22.7 | | 35 | 36 | 1.2 | 1.2 | 23.9 | | 36 | 28 | .9 | .9 | 24.8 | | 37 | 40 | 1.3 | 1.3 | 26.1 | | 38 | 35 | 1.2 | 1.2 | 27.3 | | 39 | 21 | .7 | .7 | 28.0 | | 40 | 46 | 1.5 | 1.5 | 29.5 | | 41 | 22 | .7 | .7 | 30.3 | | 42 | 41 | 1.4 | 1.4 | 31.6 | | 43 | 43 | 1.4 | 1.4 | 33.1 | | 44 | 33 | 1.1 | 1.1 | 34.2 | | 45 | 45 | 1.5 | 1.5 | 35.7 | | 46 | 38 | 1.3 | 1.3 | 36.9 | | 47 | 54 | 1.8 | 1.8 | 38.7 | | 48 | 49 | 1.6 | 1.6 | 40.4 | | 49 | 60 | 2.0 | 2.0 | 42.3 | | 50 | 103 | 3.4 | 3.4 | 45.8 | | 51 | 45 | 1.5 | 1.5 | 47.3 | | 52 | 59 | 2.0 | 2.0 | 49.2 | | 53 | 74 | 2.5 | 2.5 | 51.7 | | 54 | 58 | 1.9 | 1.9 | 53.6 | | 55 | 75 | 2.5 | 2.5 | 56.1 | | 56 | 66 | 2.2 | 2.2 | 58.3 | | 57 | 68 | 2.3 | 2.3 | 60.6 | | 58 | 62 | 2.1 | 2.1 | 62.6 | | 59 | 49 | 1.6 | 1.6 | 64.3 | | 60 | 66 | 2.2 | 2.2 | 66.5 | | 61 | 52 | 1.7 | 1.7 | 68.2 | | 62 | 56 | 1.9 | 1.9 | 70.1 | | 63 | 65 | 2.2 | 2.2 | 72.2 | | 64 | 54 | 1.8 | 1.8 | 74.0 | | 65 | 52 | 1.7 | 1.7 | 75.7 | | 66 | 40 | 1.3 | 1.3 | 77.1 | | 67 | 52 | 1.7 | 1.7 | 78.8 | | 68 | 32 | 1.1 | 1.1 | 79.9 | | 69 | 43 | 1.4 | 1.4 | 81.3 | | 70 | 41 | 1.4 | 1.4 | 82.7 | | 71 | 40 | 1.3 | 1.3 | 84.0 | | 72 | 47 | 1.6 | 1.6 | 85.6 | | 73 | 37 | 1.2 | 1.2 | 86.8 | | 74 | 23 | .8 | .8 | 87.6 | | 75 | 48 | 1.6 | 1.6 | 89.2 | | 76 | 27 | .9 | .9 | 90.1 | | 77 | 24 | .8 | .8 | 90.9 | | 78 | 22 | .7 | .7 | 91.6 | | 79 | 19 | .6 | .6 | 92.2 | | 80 | 40 | 1.3 | 1.3 | 93.5 | | 81 | 23 | .8 | .8 | 94.3 | | 82 | 23 | .8 | .8 | 95.1 | | 83 | 18 | .6 | .6 | 95.7 | | 84 | 22 | .7 | .7 | 96.4 | | 85 | 13 | .4 | .4 | 96.8 | | 86 | 10 | .3 | .3 | 97.2 | | 87 | 8 | .3 | .3 | 97.4 | | 88 | 9 | .3 | .3 | 97.7 | | 89 | 5 | .2 | .2 | 97.9 | | 90 | 5 | .2 | .2 | 98.1 | | 91 | 6 | .2 | .2 | 98.3 | | 92 | 2 | .1 | .1 | 98.3 | | 93 | 2 | .1 | .1 | 98.4 | | 94 | 1 | .0 | .0 | 98.4 | | 95 | 1 | .0 | .0 | 98.5 | | Don’t know/Refused (VOL.) | 46 | 1.5 | 1.5 | 100.0 | | Total | 3006 | 100.0 | 100.0 | |

Statistics | AGE. What is your age? | N | Valid | 2960 | | Missing | 46 |

AGE. What is your age? | | Frequency | Percent | Valid Percent | Cumulative Percent | Valid | 18 | 68 | 2.3 | 2.3 | 2.3 | | 19 | 49 | 1.6 | 1.7 | 4.0 | | 20 | 52 | 1.7 | 1.8 | 5.7 | | 21 | 30 | 1.0 | 1.0 | 6.7 | | 22 | 38 | 1.3 | 1.3 | 8.0 | | 23 | 38 | 1.3 | 1.3 | 9.3 | | 24 | 39 | 1.3 | 1.3 | 10.6 | | 25 | 38 | 1.3 | 1.3 | 11.9 | | 26 | 39 | 1.3 | 1.3 | 13.2 | | 27 | 40 | 1.3 | 1.4 | 14.6 | | 28 | 37 | 1.2 | 1.3 | 15.8 | | 29 | 39 | 1.3 | 1.3 | 17.1 | | 30 | 41 | 1.4 | 1.4 | 18.5 | | 31 | 41 | 1.4 | 1.4 | 19.9 | | 32 | 38 | 1.3 | 1.3 | 21.2 | | 33 | 36 | 1.2 | 1.2 | 22.4 | | 34 | 19 | .6 | .6 | 23.0 | | 35 | 36 | 1.2 | 1.2 | 24.3 | | 36 | 28 | .9 | .9 | 25.2 | | 37 | 40 | 1.3 | 1.4 | 26.6 | | 38 | 35 | 1.2 | 1.2 | 27.7 | | 39 | 21 | .7 | .7 | 28.4 | | 40 | 46 | 1.5 | 1.6 | 30.0 | | 41 | 22 | .7 | .7 | 30.7 | | 42 | 41 | 1.4 | 1.4 | 32.1 | | 43 | 43 | 1.4 | 1.5 | 33.6 | | 44 | 33 | 1.1 | 1.1 | 34.7 | | 45 | 45 | 1.5 | 1.5 | 36.2 | | 46 | 38 | 1.3 | 1.3 | 37.5 | | 47 | 54 | 1.8 | 1.8 | 39.3 | | 48 | 49 | 1.6 | 1.7 | 41.0 | | 49 | 60 | 2.0 | 2.0 | 43.0 | | 50 | 103 | 3.4 | 3.5 | 46.5 | | 51 | 45 | 1.5 | 1.5 | 48.0 | | 52 | 59 | 2.0 | 2.0 | 50.0 | | 53 | 74 | 2.5 | 2.5 | 52.5 | | 54 | 58 | 1.9 | 2.0 | 54.5 | | 55 | 75 | 2.5 | 2.5 | 57.0 | | 56 | 66 | 2.2 | 2.2 | 59.2 | | 57 | 68 | 2.3 | 2.3 | 61.5 | | 58 | 62 | 2.1 | 2.1 | 63.6 | | 59 | 49 | 1.6 | 1.7 | 65.3 | | 60 | 66 | 2.2 | 2.2 | 67.5 | | 61 | 52 | 1.7 | 1.8 | 69.3 | | 62 | 56 | 1.9 | 1.9 | 71.1 | | 63 | 65 | 2.2 | 2.2 | 73.3 | | 64 | 54 | 1.8 | 1.8 | 75.2 | | 65 | 52 | 1.7 | 1.8 | 76.9 | | 66 | 40 | 1.3 | 1.4 | 78.3 | | 67 | 52 | 1.7 | 1.8 | 80.0 | | 68 | 32 | 1.1 | 1.1 | 81.1 | | 69 | 43 | 1.4 | 1.5 | 82.6 | | 70 | 41 | 1.4 | 1.4 | 84.0 | | 71 | 40 | 1.3 | 1.4 | 85.3 | | 72 | 47 | 1.6 | 1.6 | 86.9 | | 73 | 37 | 1.2 | 1.3 | 88.1 | | 74 | 23 | .8 | .8 | 88.9 | | 75 | 48 | 1.6 | 1.6 | 90.5 | | 76 | 27 | .9 | .9 | 91.5 | | 77 | 24 | .8 | .8 | 92.3 | | 78 | 22 | .7 | .7 | 93.0 | | 79 | 19 | .6 | .6 | 93.6 | | 80 | 40 | 1.3 | 1.4 | 95.0 | | 81 | 23 | .8 | .8 | 95.8 | | 82 | 23 | .8 | .8 | 96.6 | | 83 | 18 | .6 | .6 | 97.2 | | 84 | 22 | .7 | .7 | 97.9 | | 85 | 13 | .4 | .4 | 98.3 | | 86 | 10 | .3 | .3 | 98.7 | | 87 | 8 | .3 | .3 | 99.0 | | 88 | 9 | .3 | .3 | 99.3 | | 89 | 5 | .2 | .2 | 99.4 | | 90 | 5 | .2 | .2 | 99.6 | | 91 | 6 | .2 | .2 | 99.8 | | 92 | 2 | .1 | .1 | 99.9 | | 93 | 2 | .1 | .1 | 99.9 | | 94 | 1 | .0 | .0 | 100.0 | | 95 | 1 | .0 | .0 | 100.0 | | Total | 2960 | 98.5 | 100.0 | | Missing | Don’t know/Refused (VOL.) | 46 | 1.5 | | | Total | 3006 | 100.0 | | |

RECODE age (MISSING=SYSMIS) (18 thru 50=1) (51 thru 97=2) INTO Rage.
VARIABLE LABELS Rage 'Recode age'.
EXECUTE.
FREQUENCIES VARIABLES=Rage /ORDER=ANALYSIS.
All three variables are attitudinal variable.
Distribution of all variables is on the chart. They are all okay to analyze however recode variable is the most good variable to analyze. Statistics | Recode age | N | Valid | 2960 | | Missing | 46 |

Recode age | | Frequency | Percent | Valid Percent | Cumulative Percent | Valid | age 18-50 | 1376 | 45.8 | 46.5 | 46.5 | | age 51-97 | 1584 | 52.7 | 53.5 | 100.0 | | Total | 2960 | 98.5 | 100.0 | | Missing | System | 46 | 1.5 | | | Total | 3006 | 100.0 | | |

Recode of the variable would be good to analyze. There is missing system which indicated 46 people but it doesn’t show in valid percent therefore we could analyze only people who were participated.
. For example, on tests, you can assume if a person left an item blank he or she either did not know the answer or did not have time to complete the test, so you would want missing answers to be recoded as zeros. You may also want to recode certain values to missing.
Other variables are okay to analyze but they are including missing system so the valid percent therefore it is harder to analyze compared to recode variable.

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