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Spss

Essay by   •  February 23, 2011  •  Term Paper  •  1,264 Words (6 Pages)  •  1,104 Views

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Introduction

This paper reports and analyses the findings of a questionnaire about TV viewing. There are eight variables to the questionnaire and these variables are a variety of scales of measurement.

Descriptive statistics provide important information about variables. Mean, median and mode measure central tendency of a variable. Although normal distribution is often assumed, that is not always the case. Graphical methods to test normality allow visualization and comparison of the distribution of a random variable. These methods are both descriptive and theory oriented. This study incorporates graphical methods, both descriptive; Stem-and-leaf plot, box plot, Histogram, and Theory; Q-Q plot.

All statistics, graphs, and cross-tabulations were prepared using the SPSS software. The data was collected on February 8, 2008 and is based on actual responses from respondents that are associated with the author.

TV hours

Descriptive Statistics

(1) Descriptive Statistics (Also, calculate the coefficient of variation)

Statistics

TV

N Valid 59

Missing 0

Variance 117.895

TV

Frequency Percent Valid Percent Cumulative Percent

Valid 2 2 3.4 3.4 3.4

5 7 11.9 11.9 15.3

6 3 5.1 5.1 20.3

7 1 1.7 1.7 22.0

8 3 5.1 5.1 27.1

10 15 25.4 25.4 52.5

14 1 1.7 1.7 54.2

15 4 6.8 6.8 61.0

17 1 1.7 1.7 62.7

20 5 8.5 8.5 71.2

21 1 1.7 1.7 72.9

22 1 1.7 1.7 74.6

23 1 1.7 1.7 76.3

24 3 5.1 5.1 81.4

25 1 1.7 1.7 83.1

26 1 1.7 1.7 84.7

28 2 3.4 3.4 88.1

30 1 1.7 1.7 89.8

33 1 1.7 1.7 91.5

38 1 1.7 1.7 93.2

40 1 1.7 1.7 94.9

42 2 3.4 3.4 98.3

43 1 1.7 1.7 100.0

Total 59 100.0 100.0

Descriptive Statistics

N Minimum Maximum Mean Std. Deviation

TV 59 2 43 15.97 10.858

Valid N (listwise) 59

(2) Histogram (Superimpose the normal curve over the histogram)

(3) Stem- and- Leaf

Hours Stem-and-Leaf Plot

Frequency Stem & Leaf

2.00 0 . 22

14.00 0 . 55555556667888

16.00 1 . 0000000000000004

5.00 1 . 55557

11.00 2 . 00000123444

4.00 2 . 5688

2.00 3 . 03

1.00 3 . 8

4.00 4 . 0223

Stem width: *

Each leaf: 1 case(s)

(4) Box Plot

(5) Test the normality of distribution (One of the methods is QQ plot)

By looking at the descriptive statistics charts, we can see that the average hours of TV watched per week (mean) is 15.97. This is due to the fact the highest frequency of TV hours is between 2 and 20 hours a week. The histogram provides us with a graphic view of the data. We can see that the bars are skewed to the left, and it is evident that most of the observations are to the left of the mean. If a variable is normally distributed, its median and mean are located at the same point exactly in the center of the box plot, and the 1st and 3rd quartiles are symmetric. This is not true with our data. It can be concluded that the hours of TV watched per week is not normally distributed.

Age

(1) Descriptive Statistics (Also, calculate the coefficient of variation)

Statistics

Age

N Valid 59

Missing 0

Descriptive Statistics

N Minimum Maximum Mean Std. Deviation

Age 59 18 90 33.58 13.472

Valid N (listwise) 59

Age

Frequency Percent Valid Percent Cumulative Percent

Valid 18 2 3.4 3.4 3.4

19 3 5.1 5.1 8.5

22 1 1.7 1.7 10.2

23 4 6.8 6.8 16.9

24 2 3.4 3.4 20.3

25 6 10.2 10.2 30.5

26 5 8.5 8.5 39.0

27 1 1.7 1.7 40.7

28 2 3.4 3.4 44.1

29 3 5.1 5.1 49.2

30 3 5.1 5.1 54.2

32 1 1.7 1.7 55.9

33 3 5.1 5.1 61.0

34 1 1.7 1.7 62.7

35 4 6.8 6.8 69.5

36 2 3.4 3.4 72.9

37 1 1.7 1.7 74.6

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