¶ … SPSS
How did you treat missing or oddly coded data, and outliers?
The SPSS function for Missing Data was used to identify any outliers or oddly coded data. The percent of missing data is high at 47.2% or 1063 potential responses to the question. The number of extremes or outliers in the high range is 220. Because the numbers are high, it would be useful to look at the raw data to determine how these answers were coded. This question is an interesting one and the pattern of responses suggests that additional analysis with this variable could reveal relationships with other factors.
What did you visually observe about your variables?
Responses to some of the questions are clustered for a number of the survey respondents. That is to say that there appear to be some respondents in the sample who are very active users of their cell phones and other respondents who barely use their cell phones.
What were the results of testing for normality for scale (interval or ratio) variables?
The Kolmogorov-Smirnov test for normality was used because of the size of N, although both Shapiro-Wilk and Kolmogorov-Smirnov statistics are shown in the data table. The p-value is
How would you summarize the descriptive statistics for each variable?
The standard error (SE) indicates the reliability of the mean. When the standard error is small, it indicates that the sample mean will actually provide a more accurate picture of the actual population mean. The larger the sample size, the smaller the standard error typically is, however, the standard deviation is not affected by sample size in this direct way. The mean for this sample is 61.38, while the standard error of the mean is 5.330. The standard error indicates that the sample mean is not very close to the true mean of the overall population. The standard deviation is relatively large (183.775) which indicates that there is considerable variation in the sample.
Looking at the skewness and kurtosis of the data indicates that it is non-normal. Estimating skewness by establishing a range of twice the standard error (.071 x 2 = 0.142) in a negative and positive direction demonstrates that the data is skewed. Similarly, establishing a range of normality to estimate the kurotsis by multiplying the standard error of Kurtosis by 2 (.142 x 2 = 02.84) and showing minus that value to plus that value.
How would you state a potential null and alternative hypotheses that might be of interest and important to the test, based on your discoveries in this data?
Ho = The number of text messages received on average each day is not related to the number of moving vehicle tickets received by drivers in the study.
Ha = The number of text messages received on average each day is related to the number of moving vehicle tickets received by drivers in the study.
DESCRIPTIVES VARIABLES=q20
/STATISTICS=MEAN SUM STDDEV VARIANCE RANGE MIN MAX SEMEAN KURTOSIS SKEWNESS.
Descriptives
Notes
Output Created
07-AUG-2015 10:17:00
Comments
Input
Data
/Users/Downloads/171243_May_2010_Cell_Phones.sav
Active Dataset
DataSet1
Filter
one>
Weight
one>
Split File
one>
N of Rows in Working Data File
Missing Value Handling
Definition of Missing
User defined missing values are treated as missing.
Cases Used
All non-missing data are used.
Syntax
DESCRIPTIVES VARIABLES=q20
/STATISTICS=MEAN SUM STDDEV VARIANCE RANGE MIN MAX SEMEAN KURTOSIS SKEWNESS.
Resources
Processor Time
00:00:00.02
Elapsed Time
00:00:00.00
[DataSet1] / Users/Downloads/171243_May_2010_Cell_Phones.sav
Descriptive Statistics
N
Range
Minimum
Maximum
Sum
Mean
Std. Deviation
Statistic
Statistic
Statistic
Statistic
Statistic
Statistic
Std. Error
Statistic
Q20. On an average day, about how many text messages do you send and receive on your cell phone?
0
72991
61.39
5.330
Valid N (listwise)
Descriptive Statistics
Variance
Skewness
Kurtosis
Statistic
Statistic
Std. Error
Statistic
Std. Error
Q20. On an average day, about how many text messages do you send and receive on your cell phone?
33773.093
4.280
.071
18.173
.142
Valid N (listwise)
DESCRIPTIVES VARIABLES=q20
/STATISTICS=MEAN SUM STDDEV VARIANCE RANGE MIN MAX SEMEAN KURTOSIS SKEWNESS.
Descriptives
Notes
Output Created
07-AUG-2015 10:17:00
Comments
Input
Data
/Users/Downloads/171243_May_2010_Cell_Phones.sav
Active Dataset
DataSet1
Filter
one>
Weight
one>
Split File
one>
N of Rows in Working Data File
Missing Value Handling
Definition of Missing
User defined missing values are treated as missing.
Cases Used
All non-missing data are used.
Syntax
DESCRIPTIVES VARIABLES=q20
/STATISTICS=MEAN SUM STDDEV VARIANCE RANGE MIN MAX SEMEAN KURTOSIS SKEWNESS.
Resources
Processor Time
00:00:00.02
Elapsed Time
00:00:00.00
[DataSet1] / Users/Downloads/171243_May_2010_Cell_Phones.sav
Descriptive Statistics
N
Range
Minimum
Maximum
Sum
Mean
Std. Deviation
Statistic
Statistic
Statistic
Statistic
Statistic
Statistic
Std. Error
Statistic
Q20. On an average day, about how many text messages do you send and receive on your cell phone?
0
72991
61.39
5.330
Valid N (listwise)
Descriptive Statistics
Variance
Skewness
Kurtosis
Statistic
Statistic
Std. Error
Statistic
Std. Error
Q20. On an average day, about how many text messages do you send and receive on your cell phone?
33773.093
4.280
.071
18.173
.142
Valid N (listwise)
MVA VARIABLES=q20
/LISTWISE.
MVA
Notes
Output Created
07-AUG-2015 10:26:38
Comments
Input
Data
/Users/gigi/Downloads/171243_May_2010_Cell_Phones.sav
Active Dataset
DataSet1
Filter
one>
Weight
one>
Split File
one>
N of Rows in Working Data File
Syntax
MVA VARIABLES=q20
/LISTWISE.
Resources
Processor Time
00:00:00.03
Elapsed Time
00:00:00.00
Univariate Statistics
N
Mean
Std. Deviation
Missing
No. Of Extremesa
Count
Percent
Low
High
q20
61.39
47.2
0
a. Number of cases outside the range (Q1-1.5*IQR, Q3 + 1.5*IQR).
Summary of Estimated Means
q20
Listwise
61.39
All Values
61.39
Summary of Estimated Standard Deviations
q20
Listwise
All Values
Listwise Statistics
Listwise Means
Number of cases q20
61.39
Listwise Covariances
q20
q20
33773.093
Listwise Correlations
q20
q20
1
GET
FILE='/Users/Downloads/May_2010_Cell_Phones.sav'.
DATASET NAME DataSet1 WINDOW=FRONT.
EXAMINE VARIABLES=q20
/PLOT BOXPLOT STEMLEAF
/COMPARE GROUPS
/STATISTICS NONE
/CINTERVAL 95
/MISSING LISTWISE
/NOTOTAL.
Explore
Notes
Output Created
07-AUG-2015 11:15:28
Comments
Input
Data
/Users/Downloads/May_2010_Cell_Phones.sav
Active Dataset
DataSet1
Filter
one>
Weight
one>
Split File
one>
N of Rows in Working Data File
Missing Value Handling
Definition of Missing
User-defined missing values for dependent variables are treated as missing.
Cases Used
Statistics are based on cases with no missing values for any dependent variable or factor used.
Syntax
EXAMINE VARIABLES=q20
/PLOT BOXPLOT STEMLEAF
/COMPARE GROUPS
/STATISTICS NONE
/CINTERVAL 95
/MISSING LISTWISE
/NOTOTAL.
Resources
Processor Time
00:00:01.25
Elapsed Time
00:00:01.00
[DataSet1] / Users/Downloads/May_2010_Cell_Phones.sav
Case Processing Summary
Cases
Valid
Missing
Total
N
Percent
N
Percent
N
Percent
Q20. On an average day, about how many text messages do you send and receive on your cell phone?
52.8%
47.2%
Q20. On an average day, about how many text messages do you send and receive on your cell phone?
Q20. On an average day, about how many text messages do you send and rec
Frequency Stem & Leaf
30.00 0 .
9.00 0 . 888
10.00 1 . 222
30.00 1 . 5555555555&
.00 1 .
.00 1 .
86.00 2 .
.00 2 .
15.00 2 . 55555
.00 2 .
.00 2 .
34.00 3 .
.00 3 .
5.00 3 . 55
.00 3 .
.00 3 .
21.00 4 .
.00 4 .
1.00 4 . & 220.00 Extremes (>=50)
Stem width: 10
Each leaf: 3 case(s) & denotes fractional leaves.
EXAMINE VARIABLES=q20
/PLOT BOXPLOT STEMLEAF NPPLOT
/COMPARE GROUPS
/STATISTICS NONE
/CINTERVAL 95
/MISSING LISTWISE
/NOTOTAL.
Explore
Notes
Output Created
07-AUG-2015 11:21:15
Comments
Input
Data
/Users/Downloads/May_2010_Cell_Phones.sav
Active Dataset
DataSet1
Filter
one>
Weight
one>
Split File
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