Question

based on this assignment: For this assignment, you will undertake an analysis based on a self-designed fictitious study that utilizes statistical methodologies. You will first develop a fictitious problem to examine - it can be anything. For example, maybe you want to look at whether scores on a standardized college placement test (like the SAT) are related to the level of income a person makes 10 years after college; Or, whether those who participate in a Leadership Training program rated as better managers compared to those who do not; Or, whether ones political affiliation is related to gender. These are just a few examples; be creative and think about what piques your interest. You might also address a problem that you may want to look at in future research for a dissertation. Your analysis report should include the following components: 1. Describe your research study. 2. State a hypothesis. 3. List and explain the variables you would collect in this study. There must be a minimum of three variables and two must meet the assumptions for a correlational analysis. 4. Create a fictitious data set that you will analyze. The data should have a minimum of 30 cases, but not more than 50 cases. 5. Conduct a descriptive data analysis that includes the following: a. a measure of central tendency b. a measure of dispersion c. at least one graph 6. Briefly interpret the descriptive data analysis. 7. Conduct the appropriate statistical test that will answer your hypothesis. It must be a statistical test covered in this course such as regression analysis, single t-test, independent t-test, cross-tabulations, Chi-square, or One-Way ANOVA. Explain your justification for using the test based on the type of data and the level of measurement that the data lends to for the statistical analysis. 8. Report and interpret your findings. Use APA style and include a statement about whether you reject or fail to reject the null hypothesis. 9. Copy and paste your data output and place it in an appendix. I want to use this data of improper payment root cause underpayment or overpayment data:

Overpayments
$40.00
$18.11
$6.98
$10.61
$0.19
$4.06
$0.25
$6.30
$0.17
$32.91
$24.28
$0.29
$85.01
$15.03
$345.79
$72.38
$288.64
$283.32
$8.89
$1.19
$62.64
$3,623.55
$912.32
$6.98
$0.00
$3,537.97
$2,223.52
$0.31
$0.29
$0.05
$227.02
$67.99
$16.56
$281.67
$1,378.06
$29.32
$35,960.48
$30,568.03
$9,094.97
$681.78
$14.68
$16.40
$54.73
$71.35
$212.44
$88.04
$118.14
$519.40
$17.57
$267.23
$2.22
$5,864.03
$4,121.02
$18,443.48
$2.93
$799.44
$298.66
$108.01
$3,301.13
$41.65
$26.05
$21.27
$153.79
$210.14
$83.35
$998.71
$238.72
$71.74
$635.91
$364.39
$1,019.93
$2,059.14
$36.23
$829.18
$7,565.78

Underpayments
$0.10
$0.06
$0.13
$0.17
$0.00
$0.00
$0.00
$0.00
$1.84
$19.53
$18.86
$17.12
$31.12
$6.15
$0.04
$11.73
$119.92
$84.68
$1.97
$0.00
$214.92
$78.84
$0.05
$1.15
$0.14
$11.57
$0.47
$289.22
$1,049.91
$6,459.34
$637.14
$0.09
$71.64
$1.74
$4.61
$7.18
$0.04
$293.79
$636.42
$0.96
$355.96
$170.65
$86.22
$706.64
$0.46
$0.59
$30.37
$5.83
$1.90
$160.43
$2.23
$11.11
$0.80
$7.20
$432.36

Answer 1

1.

This document is a scientific hypothesis report in order to investigate the “Climatic Changes” over past one decade. The climatic changes have been very fast since the development and the carbon emission rates have soaring high through out. The depleting forest cover and the exhausts from the automobiles and the industries have changed the temperature and the rainfall through out the world. The Icebergs are melting and the level of the sea water has been changing. There are a lot of climatic variations introduced as result of the global warming.
Here in this report, we would not investigate the reasons and the impacts of global warming but the point of investigation is to analyze the changes in the temperature and the rainfall, from the data related to the same. We would use many statistical means to get to the conclusion.

2.

As discussed above, there have been a lot of climatic changes through out the century. We would analyze the scenario by using the data for the two cities of Kuwait and Melbourne. We gathered the data from the climate change portal of World Bank. The portal can be reached as http://sdwebx.worldbank.org/climateportal. We have provided the tables of the data collected in Appendix-I for Kuwait and Appendix-II for Melbourne.

Now, let us suppose the null hypothesis and the alternate hypothesis for the report as:

We would calculate the means of the temperature and update the hypothesis as we proceed through the results.

3.

Data Collection methods: This is the secondary data available to us through a reliable and reputable source. Making primary data for the temperature and the rainfall would have been a time taking experience and the sample of the data collected would have lesser variations as compared to the large population of the whole century. So, we have collected the data from the historical part of the site. The data can be found out by clicking on a particular region.
Methods.

We would now, discuss the various methods we are going to use for the project. The methods have been enlisted as follows:
1. The column charts help us in the comparison of data along the identical horizontal axis.
2. The line graphs show us the rise and fall of the data along the vertical axes in a more explicit way and let us compare the variables between the two graphs.
3. Descriptive statistics give the values of different statistical values related to the data.
4. One sample t-tests compares the means of the sample with population and gives the reason whether to accept the null hypothesis.

4.

We have made the column charts of the temperature (in degree Celsius) from the data available to us in the Appendix-I and Appendix-II. Similarly, we have made the line-chart of average rainfall of the two cities from January to December during the different periods which can be found from the chart titles above the graphs. It should be noted that we have taken two different vertical axes for each of the graphs shown here, the primary vertical axis for the temperature and the secondary vertical axis for the rainfall. However, we have only one horizontal corresponding to both the vertical axes, which gives the months of a year.

Appendix-I

The data for Kuwait has been presented in the following table. Statistical data include the temperature (in degrees) and the Rainfall (in mm).
Years
1900-1930   1930-1960   1960-1990   1990-2009
Months   Temperature   Rainfall   Temperature   Rainfall   Temperature   Rainfall   Temperature   Rainfall
Jan   15.1   14.8   15.5   14.8   17.5   7.2   13.7   16.7
Feb   20.3   14.9   19.6   13.8   18.4   12.9   19.2   7.9
Mar   20.9   15.3   25.1   16.3   24.5   6.3   24.5   14
Apr   30.7   4.7   30   5   30.7   3.9   30.8   3.1
May   34.2   0.5   33.7   0.5   34   0.5   35.4   0.5
Jun   36.2   0.8   34.9   0.5   35.4   0.8   37   0.5
Jul   35.4   0.6   35.7   0.5   34.9   0.6   36.6   0.6
Aug   33.4   0.5   33   0.5   32.4   0.5   33.5   0.5
Sep   27.4   1.9   27.22   2   25.1   1.9   27.5   1.9
Oct   20.3   12.8   20.8   8.6   20.7   9.2   20.7   17.6
Nov   15.7   17.8   14.5   16.4   14.7   12.9   14.6   3.3
Dec   12.9   16.9   13.9   13.9   12.8   12.8   12.1   43.6

Appendix-II

The data for Melbourne has been presented in the following table. Statistical data include the temperature (in degrees) and the Rainfall (in mm).
Years
1900-1930   1930-1960   1960-1990   1990-2009
Months   Temperature   Rainfall(mm)   Temperature   Rainfall   Temperature   Rainfall   Temperature   Rainfall
Jan   27   93.6   27.4   79.7   26.5   93.9   26.4   40.6
Feb   24.5   89.9   25.3   47   25   56.3   26.3   63.7
Mar   21.4   29.8   21.4   18.5   21.4   27.8   21.9   43.4
Apr   18   22.5   17.9   27.4   15.8   38.1   18.8   35.3
May   14.1   24.1   15.2   30.4   14   16   14.6   21.9
Jun   12.8   21.3   14.9   24.5   14.2   30.1   14.8   26.4
Jul   15   27.1   15.8   22.4   14.5   16.3   15.5   21.5
Aug   19.5   18.4   18.8   14.6   18.2   22   18.9   15.8
Sep   21.9   21.5   22.1   29.6   22.4   16.2   22.8   17.6
Oct   26.7   16   25   28.8   23.9   31.3   26.5   15.4
Nov   28   24.2   26.1   57.8   26.4   57.6   27.8   44.7
Dec   27.4   67   26.9   79.5   27.6   49.6   28   135.8

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