Combatting Cyber Crime with Technology

Combatting Cyber Crime with Technology

Instructions/Descriptions

Combatting Cyber Crime with Technology

7-1 Discussion: Combatting Cyber Crime with Technology

With the growing number of cyber crimes, law enforcement must maintain current knowledge of technology. Locate an article or a case regarding a cyber crime. Address the following:

Briefly summarize the article or case in one paragraph.

What technology did law enforcement use to combat the crime?

Review the posts of your fellow learners and respond to at least two. In your response posts, you must do one or more of the following:

Ask an analytical question.

Offer a suggestion.

Elaborate on a particular point.

Provide an alternative opinion supported with research.

Be sure to support your initial post and follow-up posts with scholarly examples from the module readings and additional literature where appropriate. You must cite all references according to APA style.

To complete this assignment, review the Discussion Rubric document.

Big Data Project Case Study Essay

For the big data project, you can work alone or work in a group (not more than 5). The purpose of the project is for you to gain experience in applying statistical method of multiple regression.

Submission Start Date – December 6, 2019

Submission Due Date – December 12, 2019

Questions and lab hours: normal class meetings and email communications.

Project Description

The general description of this project stems from research associated with self-efficacy and its relationship with academic performance and persistent.

The standard project is to use multiple regression analysis to analyze a data set. The data set is a study of student persistent enrolling in the next semester based on Gender, Age, GPA, a 22 questionnaire on self-efficacy, and student enrollment status.

The educational researcher wants to study the relationship between student enrollment status as it relates to gender, age, GPA, and the total response to a 22 questionnaire survey.

Data Sets

The data consist of 132 students at a 2-year college. The data is in pdf format, so it will require input to Excel or conversion to Excel.

For the qualitative variables use the following to prepare data.

Gender – 0 represents female, 1 represents male

Age – 0 represents student age (18 – 25), 1 represents student age (26 – older)

GPA – student’s current grade point average

Total Q – total of the 22 questions (all question responses come from a scale of 1 – 5, where 5 high.

Enrollment status – 0 represents not enrolled, 1 represents enrolled.

Items to turn in

1. BigDataProjectTemplate Excel Sheet with the following:
2. Group Names in tab 1, list of group member names if you not working alone.
3. Capture the data from the PDF, the data should be in the Data tab. The data should be reviewed and updated, the data does have some wrong inputs so it will require updates
4. The data setup for the multiple regression should include in the tab name Data Setup for Regression
5. include a residual output, may require research ( See examples of how to use Multiple Linear Regression using Microsoft Excel)
6. The following questions are included in the BigDataProjectTemplate sheet in the tab name Questions and Answers.
7. The estimated multiple regression analysis equation.
8. Does the model work? Research this question, use the Significance F value and compare it using p-value.
9. How well does the model work? Research this question using p-values and R Square.
10. Which variables contribute to the model? Research this question using p-values.
11. General interpretation of the data and the data analysis.
12. Upload BigDataProjectTemplate as file BigDataProject your name
13. Each group member should upload as individual upload.

Combatting Cyber Crime with Technology

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