Use the six-step hypothesis testing process noted below to run and interpret a correlation analysis

Use the six-step hypothesis testing process noted below to run and interpret a correlation analysis

Use the six-step hypothesis testing process (noted below) to run and interpret a correlation analysis using SPSS.    A manager is interested in better understanding job satisfaction by studying the associations between a number of variables. These variables are age, years of experience, level of education, employee engagement, job satisfaction, and job performance levels. Part 1 She thinks there is a relationship between job satisfaction and years of experience educational level employee engagement job performance State the null and alternative hypotheses. Identify critical values for the test statistics and state the decision rule concerning when to reject or fail to reject the null hypothesis of no relationship.  Run the Pearson correlation analysis and include the correlation matrix in your assignment response.  Report and interpret the correlation coefficient and p-value for each variable paired with job satisfaction. Explain what decisions the manager might make using these findings. Part 2  She thinks that younger employees will perform at a higher level, on average.  State the null and alternative hypotheses sets. Select the significance level. Select the test statistics and calculate its value. Identify critical values for the test statistics and state the decision rule concerning when to reject or fail to reject the null hypothesis. Compare the calculated and critical values to reach a conclusion for the null hypothesis.  Explain what decisions the manager might make using these findings.  Length: 4 to 6 pages not including title and reference page References: Include a minimum of 3 scholarly resources7105Week6data3.sav