Columbia Southern University Data Analysis: Descriptive Statistics and Assumption Testing

Running head: DATA ANALYSIS 1

DATA ANALYSIS 7

Data Analysis

Tammie Witcher

Columbia Southern University

Data Analysis: Descriptive Statistics and Assumption Testing

Details of how data is collected and analyzed is presented here. The research that led to the achievement of Sun Coast objectives was done using quantitative research methods since they offer detailed insights pertaining to the study. Research design is the specific type of study that one would conduct and is usually consistent with one’s philosophical worldview and the methodological approach the researcher chooses

Correlation: Descriptive Statistics and Assumption Testing

Frequency distribution table

Histogram.

Descriptive statistics table.

Measurement scale. Causal-comparative research methods which was sometimes combined with the descriptive statistics one (Creswell & Creswell, 2018). The former was used to find the relationship between dependent and independent variables after the occurrence of any action in Sun Coast.

Measure of central tendency. The measure of central tendency majored on the mode even though both mean and median were employed for the frequency table to justify various aspects tested in the research.

Evaluation. Sun Coast’s leadership and other business objectives could render descriptive statistics significant since the researchers could use the past figures to analyze the current ones and make a sound forecast of future organizational performance.

Simple Regression: Descriptive Statistics and Assumption Testing

Frequency distribution table.

Histogram.

Descriptive statistics table.

Measurement scale. Regression analysis procedure would be appropriate for RQ3 since the variable, DB levels of work would be predicted before placing employees on-site for future contracts. There is no independent sample among those provided by this RQ.

Measure of central tendency. The measure of central tendency majored on the mode even though both mean and median were employed for the frequency table to justify various aspects tested in the research.

Evaluation. DB levels of work would be predicted before placing employees on-site for future contracts. There is no independent sample among those provided by this RQ.

Multiple Regression: Descriptive Statistics and Assumption Testing

Frequency distribution table.

Histogram.

Descriptive statistics table.

Measurement scale. The measurement for this case applied the regression procedure to use to test different hypotheses since the interest is whether a relationship exists between an independent variable (IV) and dependent variable (DV). Correlation will indicate if there is a relationship between PM size (IV) and the employee health (DV) and the magnitude of that impact if at all there is one

Measure of central tendency. The measure of central tendency majored on the mode even though both mean and median were also used.

Evaluation. The outcome involved dividing populations in Sun Coast into groups based on factors such as those who attended revised training versus those who did not among other groups.

Independent Samples t Test: Descriptive Statistics and Assumption Testing

Frequency distribution table.

Histogram.

Descriptive statistics table.

Measurement scale. This method was useful in determining whether the independent or dependent variable affected the outcome through comparison of at least 2 groups of data collected. On the other hand, Sun Coast’s leadership and other business objectives could render descriptive statistics significant since the researchers could use the past figures to analyze the current ones and make a sound forecast of future organizational performance.

Measure of central tendency. The measure of central tendency majored on the mode even though both mean and median were also used.

Evaluation. This method was used to test the hypotheses such as, the statistical relationship between the PM size and the worker’s health and the difference between return on investment exist considering four lines of service that Sun Coast offers to their customers. Interviews involved taking the respondents’ opinions pertaining to the research questions developed

Dependent Samples (Paired-Samples) t Test: Descriptive Statistics and Assumption Testing

Frequency distribution table.

Histogram.

Descriptive statistics table.

Measurement scale. The conclusive research which is in line with Sun Coast where leadership trend was monitored against its business performance. Also, researching the performance of this organization required an explanation off cause and effect relationships that variables have.

Measure of central tendency. The measure of central tendency majored on the mode even though both mean and median were also used.

Evaluation: The preferred procedure to use to test the research questions with various hypotheses such as RQ1 endeavors to evaluate whether a relationship exists between an independent variable (IV) and dependent variable (DV). Correlation will indicate if there is a relationship between PM size (IV) and the employee health (DV) and the magnitude of that impact if at all there is one.

ANOVA: Descriptive Statistics and Assumption Testing

Frequency distribution table.

Histogram.

Descriptive statistics table.

Measurement scale. The research methods which was sometimes combined with the descriptive statistics one (Creswell & Creswell, 2018). The former was used to find the relationship between dependent and independent variables after the occurrence of any action in Sun Coast.

Measure of central tendency. The measure of central tendency majored on the mode even though both mean and median were also used.

Evaluation. ANOVA procedure would be suitable for testing RQ4 and RQ5 since the variables in the two research questions are non-directional. The former tests the efficiency between two groups of employees while the latter tests the blood sugar levels among the chosen employees.

References

Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). Thousand Oaks, CA: Sage.

Statistical Table

Column2 RQ1 RQ2 RQ3 RQ4 RQ5 RQ6 35 32 30 27 26 25

Column2 RQ1 RQ2 RQ3 RQ4 RQ5 RQ6 35 32 30 27 26 25

0 0 0 0 0 0 0 0 35 32 30 27 26 25

Column2 RQ1 RQ2 RQ3 RQ4 RQ5 RQ6 35 32 30 27 26 25

Frequency Table

RQ1 RQ2 RQ3 RQ4 RQ5 RQ6 35 32 30 27 26 25

Histogram

RQ1 RQ2 RQ3 RQ4 RQ5 RQ6 35 32 30 27 26 25

Frequency Table

RQ1 RQ2 RQ3 RQ4 RQ5 RQ6 35 32 30 27 26 25

Column2 RQ1 RQ2 RQ3 RQ4 RQ5 RQ6 35 32 30 27 26 25

Histogram

RQ1 RQ2 RQ3 RQ4 RQ5 RQ6 35 32 30 27 26 25

Column2 RQ1 RQ2 RQ3 RQ4 RQ5 RQ6 35 32 30 27 26 25

Frequency Table

RQ1 RQ2 RQ3 RQ4 RQ5 RQ6 35 32 30 27 26 25

Histogram

RQ1 RQ2 RQ3 RQ4 RQ5 RQ6 35 32 30 27 26 25

Frequency Table

RQ1 RQ2 RQ3 RQ4 RQ5 RQ6 35 32 30 27 26 25

Column2 RQ1 RQ2 RQ3 RQ4 RQ5 RQ6 35 32 30 27 26 25

Histogram

RQ1 RQ2 RQ3 RQ4 RQ5 RQ6 35 32 30 27 26 25

Column2 RQ1 RQ2 RQ3 RQ4 RQ5 RQ6 35 32 30 27 26 25

Frequency Table

RQ1 RQ2 RQ3 RQ4 RQ5 RQ6 35 32 30 27 26 25

Histogram

RQ1 RQ2 RQ3 RQ4 RQ5 RQ6 35 32 30 27 26 25

 

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