Week 5 Regression Team Paper (Wages)
Week 5 Regression Team Paper (Wages)
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Date Created: 11/16/15
1 Regression Paper Regression Paper Names University of Phoenix Research and Evaluation II RES 342 Teacher 2 Regression Paper Hypothesis Statement Hypothesis Identification Analysis includes everything pragmatic and reviews the information in the gathering stage of the research. The first step is developing the research problem. The purpose of this hypothesis statement analysis focus on the Hours spent on the Internet and the number of Spam Emails these people receive. The second stage is directionality the hypothesis is not considered testable, so this study investigates the relationship between the Hours spent on the Internet and the number of Spam Emails. The final stage is to design an experiment around the research design, a testable hypothesis. Found with the design, method, approach with people who have spent Hours on the Internet and who have completed an questionnaire to provide this data set. The results discover that the Hours spent on the Internet and the number of spam received predicts intentions that increase the act as partial mediators of social presence and trust. The implications of the social context is important for understanding the relationship of how Hours spent on the Internet affects the number of Spam received. Designs enhance social presence and trust is beneficial to monitor these mediators to detect potential problems. The study provides the social context for Hours spent on the Internet and the relationship the number of Spam received establishes the mediator of trust and social presence relating. Here is a data set X is Hours spent on the Internet and Y is the number of Spam Email these people received. Find r and Interpret what this means Then generate the regression equation. Then if X = 45 find Y’ Hrs #SPAMS 3 Regression Paper P1 10 4 P2 15 6 P3 20 3 P4 20 5 P5 25 4 Regression Analysis r² 0.053 n 5 r 0.231 k 1 Dep. Std. Error 1.281 Var. #Spams ANOVA table Source SS df MS F pvalue Regression 0.2769 1 0.2769 0.17 .7088 Residual 4.9231 3 1.6410 Total 5.2000 4 Regression output confidence interval coefficient std. t p 95% 95% variables s error (df=3) value lower upper Intercept 5.2308 2.1019 2.489 .0886 1.4585 11.9201 Hrs 0.0462 0.1124 0.411 .7088 0.4037 0.3114 Lenore Bailey Date: 02/06/2011 4 Regression Paper Lenore Bailey Date: 02/06/2011 Mega Stat: Regression Analysis r=0.231 r =0.053 a=5.2308 b=0.0462 y=0.0462 (45)+5.2308 y=2.079 + 5.2308=3.1518 y=3.2 Hypothesis Test Regression analysis is used to model and analyze several variables. Regression analysis also assists in understanding how the dependent variable changes when the independent variable varies. More commonly, the regression analysis is an estimate of the staticians expectation of the dependent variable depending upon the independent variables. In this assignment, Team B is regression analysis to predict and forecast hours spent on the internet and the amount of spam received. The performance of regression analysis methods depends on the form of the datagenerating process, and how it relates to the regression approach being used. In this study, Team B determined that it would be best to use a paired test because we are measuring a variable before 5 Regression Paper and after an intervention. Team B was making the assumption that the values in both groups would be closer. The total mean for spam emails was 4.4 and the average mean hours spent on the internet was 18. The regression analysis shows that there was a decrease in spam emails as the number of hours spent on the internet increased, based on a 95% confidence interval. Results The results of Team B hypothesis test as to whether or not there is relationship between the number of hours spent on the internet and the number of spam emails received. The Regression Analysis indicates that there is a decline in the number of spam email received as the hours of internet use increase for an individual. The average number of spam emails received, as stated above, is 4.4. Based on that number we see there is a significant decline in the amount of spam received as we approached the 25 hour. Team B has begun each assignment with a null hypothesis and an alternative hypothesis. After performing the correct research, Team B will either reject or fail to reject the null hypothesis. The Team is going to make an attempt to prove that the values used are close enough to accept the null hypothesis or not close enough to choose the alternate hypothesis. Team B used the Regression Analysis tool found in Excel 2007. The research on this assignment included the number of hours an individual or individuals uses the internet and the number of spam emails received during that time. The number of hours provided to the Team ranged from five through 30. The number of spam emails ranged from three to six per hour. 6 Regression Paper References Prof. Jacob Weisberg, Prof. Dov Te'eni, Ms. Limor Arman Russo, (2010) "PAST PURCHASE AND INTENTION to PURCHASE IN ECOMMERCE: THE MEDIATION OF SOCIAL PRESENCE AND TRUST", Internet Research, Vol. 21 Iss: 1. Retrieved January 8, 2011 from http://ehis.ebscohost.emerald/intern research.com Parkes, J (2011) Week Three Lecture for Research and Evaluation 342. Retrieved February 06, 2011. Data Set for Week 5 Learning Team Assignment: Regression or time series Paper L4ANOVA.doc.(61kb) Principles and Manual Procedures for ANOVA. EXCELANOVA.doc.(317kb) Excel ANOVA Procedures
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