Table 3 : Item Total Statistics

As presented in Table 3, merging these three variables under one factor is statistically confirmed by the results of the factor analysis. The acceptable value for

2In this exercise I am going to test whether there is association between the variable drug and with two level topiramate and placebo and the variable quit smoking coded (yes) or (no). After running the analysis for computing the chi-squared I obtain three different statistical tables as follows: Case processing Summary, Drug Quit Smoking Crosstabulation, and Chi Square Test which fills the statistics.

Insert a complete data table, including appropriate significant figures and units, in the space below. Also include any observations that you made over the course of Part II.

Great a population to research this is 110 nurses .The sample of the made in using a technique simple random sampling 53 nurses who worked in chambers in-patient .Dependent variable to research this compliance nurse washing the hands ( handrub ) , while the independent variable is age , sex , length of employment , education , knowledge , a unit of work , facilities , responsibility , the presence of the head room .The results of the correlation to live with hand washing ( handrub ) p = 0.38 , showed there was no connection between the ages of with hand washing ( handrub ) , to sex p = 0.682 showed there was no connection between the sexes with hand washing ( handrub ) , for the work p = 0.079 showed there was no connection between when working with hand washing ( handrub ) , for education p = 0.000 , showed there was a correlation between education by compliance hand washing ( handrub ), For knowledge p = 0.001 show there was a correlation between knowledge by compliance washing hands ( handrub ) , to a unit of work p = 0.967 exhibit no there was a correlation between a unit of work with compliance washing hands ( handrub ) , for a line of p = 0.105 exhibit no there was a correlation between facilities with compliance washing hands ( handrub ) , to the jawap p = 0.655 show there was a correlation between the responsibility of compliance with hand washing ( handrub ) , for the presence of the head room p = 0.455 exhibit no there was a correlation between the presence of the

(10 points) As a CEO you wish to maximize the productivity of your workers. You are thinking about providing your employees with smartphones so they can be readily available to clients and increase sales. However, you are also concerned that your employees are just as likely to download apps that will distract them from their work, leading them to play games and update their social networking sites rather than focus on the job of pleasing clients. To test this you randomly select 6 employees for an experiment. You provide 3 with the new smart phone and the other 3 use their existing technology. The following chart shows their changes in sales. Based on this small sample, what is the correlation between smartphone and increase in sales? [Hint: It may help to use the spreadsheet function CORREL to calculate the correlation. Also, enter the correlation in percentage terms with no more than two decimals, but do not enter the % sign. ] {Anthony, Smartphone: Yes; change in sales 60; Kira,

With the information and numerical figures obtained, a contingency table was conducted in order to compare the variables. However, there seemed to be an abundance of information that could be arranged in a different manner in order for the comparison to be uncomplicated and easy to interpret. To precisely illustrate the numerical figures and precisely compare both variables it is necessary to condense the information. First,

Now we need to check whether or not the calculated chi-square probability, p is less than or equal to α = 0.05 OR the Chi-Square value, χ2 from chi-square distribution tables is equal to or greater than α = 0.05. If p α OR χ2 α, we reject the null hypothes is and conclude that at the 0.05 significance level, there is a relationship between the row variables and column variables. Since p = 0.04285 < α = 0.05 (OR χ2 = 11.1 > α = 0.05) we conclude

the correlation model b. the regression model c. correlation analysis d. None of these alternatives is correct. ANS: B 18. a. b. c. d. ANS: B 19. a. b. c. d. Larger values of r2 imply that the observations are more closely grouped about the average value of the independent variables average value of the dependent variable least squares line origin In regression analysis, the independent variable is used to predict other independent variables used to predict the dependent variable called the intervening variable the variable that is being predicted In regression analysis, the variable that is being predicted is the dependent variable independent variable intervening variable is usually x

  | df | SS | MS | F | Significance F | | | |

* Unknown values in the sales column was calculated by adding the residual (column F) and predicted value (column E)

Data Summary Table 2.1. Descriptive Statistics for Data from Medical 1 (Good Health) |Alpha value (for confidence interval) |0.02 | | | | | |Variable #1 (Florida) | | | |Count |20 |Skewness |-0.2526 |Confidence Level: | | | | | | |1.1992 | | |Mean |5.55 |Skewness Standard Error |0.48582 | | | |Mean LCL |4.33525

a. Correlate computing those variables from the data available in normalized tables arranged in row x columns.

SPSS for Windows® Intermediate & Advanced Applied Statistics Zayed University Office of Research SPSS for Windows® Workshop Series Presented by Dr. Maher Khelifa Associate Professor Department of Humanities and Social Sciences College of Arts and Sciences

Data cleaning was included throughout the process of this correlational study, and it included checking for duplicate data and checking for internal consistency. Data editing and omission was used while analyzing data and some statistical outliers were found, this explains why some of the collected information about other networks was not mentioned in the statistical test results. Data analysis included descriptive statistics about the sample, and the statistical analysis included a T-test and a Pearson r Correlation test.

Additionally, the data in the hypothesis test for correlation section has a p-value of 0.000. In other words, the decision is to reject the null hypothesis, but with a conclusion that some correlation exists between the variables. In brief, the ANOVA section displays figure for SS, df, Ms, F, and F crit. The regression SS figure computed are 16.1864 for SS, 1 for df, 16.1864 for MS, 1168.8879 for F and 3.8889 for F crit. The error SS stands at 2.7418, 198 for df and 0.0138 for MS. Finally,