Research Methods
marmaydec
Unit4.docx
Descriptive Statistics Analysis
Student’s Name
Institution
Date
Descriptive Statistics Analysis
Introduction
The Sub Coast Remediation data description by use of the descriptive statistics tools as explained in our previous classes. We are establishing whether the assumptions have been met in using the parametric statistical procedures. We shall repeat for every tab in the “Sun Coast Remediation Research Study”.
Descriptive assumptions and data; correlation
The frequency distribution table
“Running head: DESCRIPTIVE STATISTICS ANALYSIS” 1
“DESCRIPTIVE STATISTICS ANALYSIS” 17
|
The size of PM |
The frequency |
|
Zero to four |
eight |
|
Two to four |
Twenty-four |
|
Five to seven |
Thirty-seven |
|
Eight to ten |
Thirty-four |
|
The sick days |
Frequency |
|
Zero to two |
One |
|
Four to seven |
Sixty-one |
|
Eight to nine |
thirty |
|
Ten to twelve |
eleven |
The histogram
Descriptive Statistics Table
|
microns |
|
|
sick day |
|
|
|
|
|
|
|
|
“Mean |
5.65728155 |
|
Mean |
7.126214 |
|
Standard Error |
0.25560014 |
|
Standard Error |
0.186484 |
|
Median |
6 |
|
Median |
7 |
|
Mode |
8 |
|
Mode |
7 |
|
Standard Deviation |
2.59405814 |
|
Standard Deviation |
1.892605 |
|
Sample Variance |
6.72913764 |
|
Sample Variance |
3.581953 |
|
Kurtosis |
-0.8521619 |
|
Kurtosis |
0.124923 |
|
Skewness |
-0.37325713 |
|
Skewness |
0.14225 |
|
Range |
9.8 |
|
Range |
10 |
|
Minimum |
0.2 |
|
Minimum |
2 |
|
Maximum |
10 |
|
Maximum |
12 |
|
Sum |
582.7 |
|
Sum |
734 |
|
Count |
103 |
|
Count |
103 |
|
Largest (1) |
10 |
|
Largest (1) |
12 |
|
Smallest (1) |
0.2 |
|
Smallest (1) |
2 |
|
Confidence Level (95.0%) |
0.50698167 |
|
Confidence Level(95.0%) |
0.36989” |
The test of Kolmogorov Smirnov
The hypotheses can be analyzed as follows;
H1: the sample data is not substantially different than the normal population
H2: the sample data is substantially different than the normal population
The Skewness of 0.37 and the Kurtosis a negative 0.85 are all near to zero within the range negative two to positive two and the suggestion is that the data is symmetrical. This can be confirmed by the median and the mean similarity.
Accepting the null hypothesis
The scale measurement
The ordinal
Central tendency measurement
The first one is mean
The evaluation
The normal distributions portray the data graph being of the bell curve. The data is always symmetrical around the kurtosis being equal to zero and it's mean as well.
The descriptive assumptions and data; the simple regression
Table of frequency distribution
|
Expenditure |
Frequency |
|
20-500 |
108 |
|
501-1000 |
76 |
|
1001-1500 |
27 |
|
1501-2000 |
11 |
|
2001-2500 |
1 |
|
The time |
The frequency |
|
Zero to fifty |
six |
|
Fifty-one to hundred |
Twenty-six |
|
One hundred and one to two hundred |
Ninety-eight |
|
Two hundred and one to three |
Eighty-five |
|
Three hundred and one to four hundred |
Eight |
The histogram
The table of descriptive statistics
|
safety training expenditure |
|
|
lost time hours |
|
|
|
|
|
|
|
|
“Mean |
595.9843812 |
|
Mean |
188.0045 |
|
Standard Error |
31.4770075 |
|
Standard Error |
4.803089 |
|
Median |
507.772 |
|
Median |
190 |
|
Mode |
234 |
|
Mode |
190 |
|
Standard Deviation |
470.0519613 |
|
Standard Deviation |
71.72542 |
|
Sample Variance |
220948.8463 |
|
Sample Variance |
5144.536 |
|
Kurtosis |
0.444080195 |
|
Kurtosis |
-0.50122 |
|
Skewness |
0.951331922 |
|
Skewness |
-0.08198 |
|
Range |
2251.404 |
|
Range |
350 |
|
Minimum |
20.456 |
|
Minimum |
10 |
|
Maximum |
2271.86 |
|
Maximum |
360 |
|
Sum |
132904.517 |
|
Sum |
41925 |
|
Count |
223 |
|
Count |
223 |
|
Largest(1) |
2271.86 |
|
Largest(1) |
360 |
|
Smallest(1) |
20.456 |
|
Smallest(1) |
10 |
|
Confidence Level(95.0%) |
62.03197147 |
|
Confidence Level(95.0%) |
9.465484” |
The test of Kolmogorov Smirnov
The hypotheses can be analyzed as follows;
H1: the sample data is not substantially different than the normal population
H2: the sample data is substantially different than the normal population
The Skewness of 0.37 and the Kurtosis a negative 0.85 are all near to zero within the range negative two to positive two and the suggestion is that the data is symmetrical. This cannot be confirmed by the median and the mean similarity.
Rejecting the null hypothesis
The scale measurement
The nominal
Central tendency measurement
The first one is the media
The evaluation
The normal distributions portray the data graph being of the bell curve. The data is always symmetrical around the kurtosis being equal to zero and it's mean as well.
The descriptive assumptions and data: The multiple regression
The table of frequency distribution
|
Decibel |
Frequency |
|
100-106 |
4 |
|
107-111 |
51 |
|
112-116 |
126 |
|
117-121 |
249 |
|
122-131 |
786 |
|
132-141 |
287 |
Histogram
The table of descriptive statistics
|
“Decibel |
|
|
|
|
|
Mean |
124.8359 |
|
Standard Error |
0.177945 |
|
Median |
125.721 |
|
Mode |
127.315 |
|
Standard Deviation |
6.898657 |
|
Sample Variance |
47.59146 |
|
Kurtosis |
-0.31419 |
|
Skewness |
-0.41895 |
|
Range |
37.607 |
|
Minimum |
103.38 |
|
Maximum |
140.987 |
|
Sum |
187628.4 |
|
Count |
1503” |
The test of Kolmogorov Smirnov
The hypotheses can be analyzed as follows;
H1: the sample data is not substantially different than the normal population
H2: the sample data is substantially different than the normal population
The Skewness of 0.37 and the Kurtosis a negative 0.85 are all near to zero within the range negative two to positive two and the suggestion is that the data is symmetrical. This can be confirmed by the median and the mean similarity.
Accepting the null hypothesis
The scale measurement
Internal
Central tendency measurement
The first one is mean
The evaluation
The normal distributions portray the data graph being of the bell curve. The data is always symmetrical around the kurtosis being equal to zero and it's mean as well.
The descriptive assumptions and data; the independent samples t-test
Descriptive Data and Assumptions: Independent Samples t-Test
Frequency Distribution Table
|
Training |
Frequency |
|
49-60 |
12 |
|
61-70 |
20 |
|
71-80 |
21 |
|
81-90 |
8 |
|
91-100 |
1 |
|
Training |
Frequency |
|
74-80 |
14 |
|
81-85 |
21 |
|
86-90 |
19 |
|
91-95 |
6 |
|
96-100 |
2 |
Histogram
The table of descriptive statistics
|
“Prior Training |
|
|
Revised Training |
|
|
|
|
|
|
|
|
Mean |
69.79032 |
|
Mean |
84.77419 |
|
Standard Error |
1.402788 |
|
Standard Error |
0.659479 |
|
Median |
70 |
|
Median |
85 |
|
Mode |
80 |
|
Mode |
85 |
|
Standard Deviation |
11.04556 |
|
Standard Deviation |
5.192742 |
|
Sample Variance |
122.0045 |
|
Sample Variance |
26.96457 |
|
Kurtosis |
-0.77668 |
|
Kurtosis |
-0.35254 |
|
Skewness |
-0.0868 |
|
Skewness |
0.144085 |
|
Range |
41 |
|
Range |
22 |
|
Minimum |
50 |
|
Minimum |
75 |
|
Maximum |
91 |
|
Maximum |
97 |
|
Sum |
4327 |
|
Sum |
5256 |
|
Count |
62 |
|
Count |
62 |
|
Largest(1) |
91 |
|
Largest(1) |
97 |
|
Smallest(1) |
50 |
|
Smallest(1) |
75 |
|
Confidence Level(95.0%) |
2.805048 |
|
Confidence Level(95.0%) |
1.31871” |
The test of Kolmogorov Smirnov
The hypotheses can be analyzed as follows;
H1: the sample data is not substantially different than the normal population
H2: the sample data is substantially different than the normal population
The Skewness and the Kurtosis are all near to zero within the range negative two to positive two and the suggestion is that the data is symmetrical. This can be confirmed by the median and the mean similarity.
Accepting the null hypothesis
The scale measurement
Internal
Central tendency measurement
The first one is mean
The evaluation
The normal distributions portray the data graph being of the bell curve. The data is always symmetrical around the kurtosis being equal to zero and it's mean as well.
Descriptive assumption and data: Dependent Samples t-Test
the table of frequency distribution
|
Exposure |
Frequency |
|
5-15 |
5 |
|
16-25 |
8 |
|
26-35 |
12 |
|
Exposure |
Frequency |
|
5-15 |
5 |
|
16-25 |
8 |
|
26-35 |
11 |
|
36-45 |
17 |
|
46-56 |
8 |
Histogram
The table of descriptive statistics
|
“Pre-Exposure μg/dL |
|
|
Post-Exposure μg/dL |
|
|
|
|
|
|
|
|
Mean |
32.8571429 |
|
Mean |
33.28571 |
|
Standard Error |
1.75230655 |
|
Standard Error |
1.781423 |
|
Median |
35 |
|
Median |
36 |
|
Mode |
36 |
|
Mode |
38 |
|
Standard Deviation |
12.2661458 |
|
Standard Deviation |
12.46996 |
|
Sample Variance |
150.458333 |
|
Sample Variance |
155.5 |
|
Kurtosis |
-0.57603713 |
|
Kurtosis |
-0.65421 |
|
Skewness |
-0.42510965 |
|
Skewness |
-0.48363 |
|
Range |
50 |
|
Range |
50 |
|
Minimum |
6 |
|
Minimum |
6 |
|
Maximum |
56 |
|
Maximum |
56 |
|
Sum |
1610 |
|
Sum |
1631 |
|
Count |
49 |
|
Count |
49 |
|
Largest(1) |
56 |
|
Largest(1) |
56 |
|
Smallest(1) |
6 |
|
Smallest(1) |
6 |
|
Confidence Level(95.0%) |
3.52324845 |
|
Confidence Level(95.0%) |
3.581792” |
The test of Kolmogorov Smirnov
The hypotheses can be analyzed as follows;
H1: the sample data is not substantially different than the normal population
H2: the sample data is substantially different than the normal population
The Skewness and the Kurtosis are all near to zero within the range negative two to positive two and the suggestion is that the data is symmetrical. This can be confirmed by the median and the mean similarity.
Accepting the null hypothesis
The scale measurement
Interval
Central tendency measurement
The first one is mean
The evaluation
The normal distributions portray the data graph being of the bell curve. The data is always symmetrical around the kurtosis being equal to zero and it's mean as well
The descriptive assumption and data: THE ANOVA
The table of frequency distribution
|
Air |
Frequency |
|
1-3 |
1 |
|
4-6 |
4 |
|
7-9 |
6 |
|
10-12 |
7 |
|
12-15 |
2 |
|
Soil |
Frequency |
|
5-7 |
3 |
|
8-10 |
13 |
|
10-13 |
4 |
|
Water |
Frequency |
|
1-3 |
1 |
|
4-6 |
10 |
|
7-9 |
5 |
|
10-12 |
4 |
|
Training |
Frequency |
|
1-3 |
1 |
|
4-6 |
16 |
|
7-9 |
3 |
Histogram
Descriptive Statistics Table
|
A = Air |
|
|
B = Soil |
|
|
|
|
|
|
|
|
“Mean |
8.9 |
|
Mean |
9.1 |
|
Standard Error |
0.684028 |
|
Standard Error |
0.390007 |
|
Median |
9 |
|
Median |
9 |
|
Mode |
11 |
|
Mode |
8 |
|
Standard Deviation |
3.059068 |
|
Standard Deviation |
1.744163 |
|
Sample Variance |
9.357895 |
|
Sample Variance |
3.042105 |
|
Kurtosis |
-0.6283 |
|
Kurtosis |
0.11923 |
|
Skewness |
-0.36085 |
|
Skewness |
0.492002 |
|
Range |
11 |
|
Range |
7 |
|
Minimum |
3 |
|
Minimum |
6 |
|
Maximum |
14 |
|
Maximum |
13 |
|
Sum |
178 |
|
Sum |
182 |
|
Count |
20 |
|
Count |
20 |
|
Largest(1) |
14 |
|
Largest(1) |
13 |
|
Smallest(1) |
3 |
|
Smallest(1) |
6 |
|
Confidence Level(95.0%) |
1.431688 |
|
Confidence Level(95.0%) |
0.816294” |
|
C = Water |
|
|
D = Training |
|
|
|
|
|
|
|
|
“Mean |
7 |
|
Mean |
5.4 |
|
Standard Error |
0.575829 |
|
Standard Error |
0.265568 |
|
Median |
6 |
|
Median |
5 |
|
Mode |
6 |
|
Mode |
5 |
|
Standard Deviation |
2.575185 |
|
Standard Deviation |
1.187656 |
|
Sample Variance |
6.631579 |
|
Sample Variance |
1.410526 |
|
Kurtosis |
-0.23752 |
|
Kurtosis |
0.253747 |
|
Skewness |
0.760206 |
|
Skewness |
0.159183 |
|
Range |
9 |
|
Range |
5 |
|
Minimum |
3 |
|
Minimum |
3 |
|
Maximum |
12 |
|
Maximum |
8 |
|
Sum |
140 |
|
Sum |
108 |
|
Count |
20 |
|
Count |
20 |
|
Largest(1) |
12 |
|
Largest(1) |
8 |
|
Smallest(1) |
3 |
|
Smallest(1) |
3 |
|
Confidence Level(95.0%) |
1.205224 |
|
Confidence Level(95.0%) |
0.55584” |
The test of Kolmogorov Smirnov
The hypotheses can be analyzed as follows;
H1: the sample data is not substantially different than the normal population
H2: the sample data is substantially different than the normal population
The Skewness and the Kurtosis are all near to zero within the range negative two to positive two and the suggestion is that the data is symmetrical. This can be confirmed by the median and the mean similarity.
Accepting the null hypothesis
The scale measurement
Ratio
Central tendency measurement
The first one is mean
The evaluation
The normal distributions portray the data graph being of the bell curve. The data is always symmetrical around the kurtosis being equal to zero and it's mean as well
References
Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approach (5th ed.). Thousand Oaks, CA: Sage. Retrieve from chrome-extension://ohfgljdgelakfkefopgklcohadegdpjf/http://www.drbrambedkarcollege.ac.in/sites/default/files/research-design-ceil.pdf
Appendix
Copy and paste your Kolmogorov-Smirnov Test table and results from Excel into this appendix.
Histogram for Correlation
Frequency 1 4 7 10 More 8 24 37 34 0PM size
Annual Sick Days
Frequency 2 7 9 12 More 1 61 30 11 0Sick Days
Frequency
Training Expenditure
Frequency 500 1000 1500 2000 2275 More 108 76 27 11 1 0
Expenditure
Frequency
Lost time hours
Frequency 50 100 200 300 400 More 6 26 98 85 8 0Time
Frequency
Sound Level
Frequency 106 111 116 121 131 141 More 4 51 126 249 786 287 0Decibles
Frequency
Histogram Training t Test
Frequency 60 70 80 90 100 More 12 20 21 8 1 0Training
Frequency
Histogram training
Frequency 80 85 90 95 100 More 14 21 19 6 2 0Training
Frequency
Histogram Sample data 2
Frequency 15 25 35 45 56 More 5 8 11 17 8 0t test
Frequency
Histogram Paired Sample Data
Frequency 15 25 35 45 56 More 5 8 12 16 8 0t test
Frequency
Histogram Air
Frequency 3 6 9 12 15 More 1 4 6 7 2 0Air
Frequency
Histogram Soil
Frequency 7 10 13 More 3 13 4 0Soil
Frequency
Histogram Water
Frequency 3 6 9 12 More 1 10 5 4 0Water
Frequency
Histogram Training
Frequency 3 6 9 More 1 16 3 0Training
Frequency
“Running head: DESCRIPTIVE STATISTICS ANALYSIS”
1
Descriptive Statistics Analysis
Student’s Name
Institution
Date
“Running head: DESCRIPTIVE STATISTICS ANALYSIS”
1
Descriptive Statistics Analysis
Student’s Name
Institution
Date
