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Instructions
Descriptive Statistics Analysis
Describe the Sun Coast data using the descriptive statistics tools discussed in the unit lesson. Establish whether assumptions are met to use parametric statistical procedures. Repeat the tasks below for each tab in the Sun Coast research study data set. Utilize the Unit IV Scholarly Activity template attach.
You will utilize Microsoft Excel ToolPak. The links to the ToolPak are here.
Here are some of the items you will cover.
Produce a frequency distribution table and histogram.
Generate descriptive statistics table, including measures of central tendency (mean, median, and mode), kurtosis, and skewness.
Describe the dependent variable measurement scale as nominal, ordinal, interval, or ratio.
Analyze, evaluate, and discuss the above descriptive statistics in relation to assumptions required for parametric testing. Confirm whether the assumptions are met or are not met.
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Problems Encountered by Sun Coast Remediation
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Data Analysis: Descriptive Statistics and Assumption Testing
Statistics involves the process of collection, analysis, interpretation, presentation, and data organization in a way that can be understood by its users. Statistical analyses are divided into two broad categories: the inferential and descriptive statistics (Verma & Abdel-Salam, 2019). Descriptive statistics consists of the methods of data representation that calculates descriptive figures and summary graphs or both. The Sun Coast Remediation data was analyzed and presented using descriptive statistics with the interpretations to ascertain whether parametric statistical procedures were met.
Correlation: Descriptive Statistics and Assumption Testing
The analysis of Sun Coast Remediation data yielded the following statistical descriptive figures and summary graphs.
Frequency distribution table
| Sick Days | Frequency |
| 2 | 1 |
| 3 | 1 |
| 4 | 5 |
| 5 | 13 |
| 6 | 18 |
| 7 | 24 |
| 8 | 18 |
| 9 | 12 |
| 10 | 7 |
| 11 | 2 |
| More | 2 |
Histogram
Descriptive statistics table
| Mean Annual Sick Days Per Employee | |
| Mean | 7.126213592 |
| Standard Error | 0.186483898 |
| Median | 7 |
| Mode | 7 |
| Standard Deviation | 1.892604864 |
| Sample Variance | 3.58195317 |
| Kurtosis | 0.124922603 |
| Skewness | 0.142249784 |
| Range | 10 |
| Minimum | 2 |
| Maximum | 12 |
| Sum | 734 |
| Count | 103 |
Measurement scale
The frequency distribution tables provide a means of ascertaining the measurement scales in which the data was measured. An analysis of the variables used in data (sick days) revealed that the measurement scale used is ratio scale. Argyrols (2011) points out that a ratio scale uses units that measure equal distance between values on the scale with unique zero. The variables used indicate sick days with an interval of 1 and with a unique zero as a starting point since there can be zero sick days.
Measure of central tendency
The measures of central tendency are a summary statistic that provides center point of a data set (Argyrous, 2011). The measures of central tendency used in the descriptive statistics for Sun Coast Remediation data are mean, mode, and media. These measures provide the mid-point in which the sick days are dispersed and this can be deduced from the histogram as the mid-point from which the data sets are dispersed.
Evaluation
The assumptions for parametric assumptions can be ascertained if it were met by checking the histogram curve and the centrality of the distribution of the data. First, the measures of central tendency must be same. In the descriptive statistics, the mean, mode, and median are all same (7). Secondly, observing the histogram shows that the data is evenly distributed with no outliers. Lastly, the observed values for skewness and kurtosis are 0.142249784 and 0.124922603, which are all closer to zero. The general assumption is that the closer the values of skewness and kurtosis to zero, parametric statistical testing can be evaluated using such data. Therefore, the descriptive statistics above met the requirements of parametric assumptions.
Simple Regression: Descriptive Statistics and Assumption Testing
Frequency distribution table
| Lost Time | Frequency |
| 10 | 1 |
| 35 | 1 |
| 60 | 9 |
| 85 | 9 |
| 110 | 17 |
| 135 | 18 |
| 160 | 24 |
| 185 | 27 |
| 210 | 37 |
| 235 | 24 |
| 260 | 21 |
| 285 | 15 |
| 310 | 12 |
| 335 | 4 |
| More | 4 |
Histogram
Descriptive statistics table
| Lost Time Hours | |
| Mean | 188.0044843 |
| Standard Error | 4.803089447 |
| Median | 190 |
| Mode | 190 |
| Standard Deviation | 71.72542099 |
| Sample Variance | 5144.536016 |
| Kurtosis | -0.501223533 |
| Skewness | -0.081984874 |
| Range | 350 |
| Minimum | 10 |
| Maximum | 360 |
| Sum | 41925 |
| Count | 223 |
Measurement scale
The data set in the variables are ordered with meaningful intervals between the data values without unique zero, meaning it used an interval measurement scale. The measures of lost time cannot have zero starting point, since one cannot say that there is zero lost time.
Measure of central tendency The measures of central tendency employed are mean, mode, and median. The measures provided how the data is evenly distributed across the………………………………………………………………………………………………
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