statistics

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Arizona State University School of Criminology and Criminal Justice CRJ 511 Applied Data Analysis in Criminal Justice Final Project Use SENTENCING.XLS. A codebook with description of the data is on the last page of this document. Note: 1. Read each step carefully. 2. You are expected to use Excel to conduct appropriate statistical analysis to answer each question in this project. 3. Please copy and paste your results from Excel into WORD first. Type your summary afterwards. Your summary needs to be articulate to a reader who does not read and understand Excel output. Remember that the instructor expects more than just Excel output. Tasks to Complete: 1. Produce a frequency table and a pie chart for RACE. Summarize the results. (Note that 0 = White and 1= Black). 2. Produce the mode, median, mean, standard deviation, variance, range, minimum, and maximum for JAILCREDIT and AGEADMIT. Report the results. 3. Construct a 95% confidence interval around the sample mean of JAILCREDIT and AGEADMIT, respectively. Interpret and summarize your results. 4. Assume that the average age of offenders at prison admissions in the state of Florida is 30. Use the data to perform a hypothesis test to determine if the average age of offenders at prison admissions in your sample is significantly different from the average age in the offender population in Florida. The variable that measures the average age of offenders at prison admission is AGEADMIT. Use a .05 level of statistical significance. Run the one-sample t-test in Excel. In your summary, please discuss the null hypothesis, alternative hypothesis, the result of this hypothesis test, and interpret the result. 5. Assume that the average length of jail in pretrial in the state of Florida is 90 days. Use the data to perform a hypothesis test to determine if the average length of jail in pretrial in your sample is significantly different from the average length of jail in pretrial in Florida. The variable that measures the average length of jail in pretrial is JAILCREDIT. Use a .05 level of statistical significance. Run the one-sample t-test in Excel. In your summary, please discuss the null hypothesis, alternative hypothesis, the result of this hypothesis test, and interpret the result. 6. Conduct an independent sample t-test (alpha= .05) in Excel to determine whether there is a significant difference in the length of jail in pretrial between White and Black offenders. For this t-test, assume that the variances of the two groups are unequal. In your summary, please discuss the null hypothesis, alternative hypothesis, the result of this hypothesis test, and interpret the result. 7. Conduct an independent sample t-test (alpha= .05) in Excel to determine whether there is a significant difference in the age of offenders at prison admissions between White and Black offenders. For this t-test, assume that the variances of the two groups are equal. In your summary, please discuss the null hypothesis, alternative hypothesis, the result of this hypothesis test, and interpret the result. 8. Conduct a Chi-Square test in Excel to determine if the race of offenders is independent of offense type. In your summary, please discuss the null hypothesis, alternative hypothesis, the result of this hypothesis test, and interpret the result. 9. Conduct an ANOVA test in Excel to determine if there is a significant difference in JAILCREDIT across offense types. In your summary, please discuss the null hypothesis, alternative hypothesis, the result of this hypothesis test, and interpret the result. 10. Correlate AGEADMIT and JAILCREDIT in Excel. Summarize your results and make sure that you briefly explain what this correlation means to you in terms of the impact of age on the length of jail in pretrial (direction of the correlation, correlation coefficient, and test of significance result). Variable Name Type of Variable Variable Label Value Labels Values Explanation County Character County of Sentence NA Literal name of county Sex Character Sex of Offender NA Literal name of sex – Male, Female Race Character Race of Offender NA Literal name of race – White, Black, Chinese, Nat. Amer. Hispanic, All Others, Unknown Sentence Numeric Length of Sentence in Months NA Sentence length in months, except 9999998 = Life, 9999999 = Death Offense Numeric Primary Offense 1 = Murder 2 = Sex Offense 3 = Robbery 4 = Other Violent 5 = Burglary 6 = Property 7 = Drugs 8 = Weapons 9 = Other Crimes JailCredit Numeric Length in Jail Pretrial NA In Days AgeAdmit Numeric Age of Offender at Prison Admissions NA In Years What your data should look like (the first few rows only) COUNTY SEX RACE SENTENCE OFFENSE JAILCREDIT AGEADMIT LEE MALE WHITE 300 2 388 65 PALM BEACH MALE BLACK 39 7 272 61 BROWARD MALE BLACK 12 5 75 59 POLK MALE WHITE 36 4 224 71 HILLSBOROUGH MALE BLACK 120 2 225 59 DADE MALE BLACK 20 4 135 66 BROWARD MALE BLACK 17 7 53 56 ESCAMBIA MALE BLACK 36 7 90 58