How can operating system data be used to track criminal activity?
Tracking Criminal Activity How can operating system data be used to track criminal activity? Use specific examples of operating system information (i.e., an Internet history cache) in your response.
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- Application 4: Correlations Order Description Application 4: Correlations This week, you explore key statistical concepts related to data and problem solving through the completion of the following exercises using SPSS and the information found in your Statistics and Data Analysis for Nursing Research textbook. The focus of this assignment will be on correlation coefficients, tools that can help to determine the strength of the relationship between variables. Because multiple factors influence health care variables, it is important for you to understand how to calculate and interpret correlation coefficients. To prepare: Review the Statistics and Data Analysis for Nursing Research chapters that you read as a part of the Week 6 Learning Resources. As you do so, pay close attention to the examples presented—they provide information that will be useful for you to recall when completing the software exercises. You may also wish to review the Research Methods for Evidence-Based Practice video resources. Refer to the Week 6 Correlations Exercises and follow the directions to calculate correlational statistics using Polit2SetB.sav data set. Compare your data output against the tables presented in the Week 6 Correlations Exercises SPSS Output document. Formulate an initial interpretation of the meaning or implication of your calculations. To complete: Complete the Part I and Part II steps and Assignments as outlined in the Week 6 Correlations Exercises page. Save your Application in one document as a ".doc" or ".rtf" file with the filename "APP4+last name+first initial". For example, Sally Ride's assignment filename would be "APP4RideS". Please use the link below to submit your assignment. Required Resources
- Question: Q: Chapter Chapter 11 of Mertler and Vannata; answer exercises on pages 306 and 307: This exercise utilizes the SPSS data setprofile-e.sav, which can be downloaded from this Web site: www.Pvrczak.com/data Conduct a Forward: LR logistic regression analysis with the following variables: IV—age, educ, hrsl, sibs, rincom91, life2 (categorical) DV—satjob2 Note: The variable Iife2 is categorical such that dull = 1, routine/exciting = 2, and all other values are system missing. Develop a research question for the following scenario. Conduct a preliminary Linear Regression to identify outliers and evaluate multicollinearity among the five continuous variables . Complete the following: a. Using the Chi-Square table in Appendix B, identify the critical value atp< .001 for identifying outliers. Use Explore to determine if there are outliers. Which cases should be eliminated? b. Is multicollinearity a problem among the five continuous variables? Conduct Binary Logistic Regression using the Forward: LR method. IV—age, educ, hrsl, sibs, rincom91, life2 (categorical; last is the reference category) DV—satjob2 Note: Make sure that any outliers identified in Exercise 2a are removed from data before running the logistic regression. Also, designating life2 as a categorical covariate with the last category as the reference, essentially makes "routine/exciting" = 0 and "dull" = 1, so interpret the results accordingly. a. Which variables were entered into the model? b. To what degree does the model fit the data? Explain. c. Is the generated model significantly different from the constant-only model? d. How accurate is the model in predicting job satisfaction? e. What are the odds ratios for the model variables? Explain. Module 14 – Multi-level linear analyses: When do you use multi-level linear analyzes? Chapter 8 of Cronk (chapter below I wasn’t sure what was being asked) and answer all practice exercises; post your results here:
- You will be examining the data-set labelled AutoDiscount2y15, which has tracked automobile sales records, keeping track of some information about the purchaser (gender, income [units, $], and age [units, years]) as well as the discount (advertised price l
- Kiosk Inventory Project Description: In this project, you will create database objects to track the inventory of items for sale in a kiosk located in a college snack bar. You will create a table and import data from Excel to create a second table. You will create a simple query, a form, and a report.
- Visit the U.S. Government Web site, TradeStats Express:http://tse.export.gov/TSE/TSEReports.aspx?DATA=NTD Find National Trade Data. Determine the trade balance between the U.S. and China for the most recent five year period. Illustrate the trend over this period with a graph of the data.
