Refer to the data in images. Test for a significant difference in the variances of the initial white blood cell count between patients who did and patients who did not receive a bacterial culture.
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Refer to the data in images.
Test for a significant difference in the variances of the
initial white blood cell count between patients who did and
patients who did not receive a bacterial culture.
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- The data shown below consists of the price (in dollars) of 11 events at a local venue and the number of people who attended. Determine if there is significant linear correlation between ticket price and number of attendees. Use a significance level of 0.10 and round all values to 4 decimal places. Ticket Price Attendence 6 239 10 148 14 101 18 77 22 64 26 57 30 54 34 52 38 51 42 51 46 50 Ho: ρ = 0Ha: ρ ≠ 0 Find the Linear Correlation Coefficient r = Find the p-value p-value = The p-value is Less than (or equal to) αα Greater than αα The p-value leads to a decision to Accept Ho Do Not Reject Ho Reject Ho The conclusion is There is no Significant Linear Correlation between ticket price and attendence. There is no Significant Correlation There is Significant Positive Linear Correlation between ticket price and attendence. There is Significant Linear Correlation between ticket price and attendence. There is Significant Negative Linear…The maximum weights (in kilograms) for which one repetition of a half-squat can be performed and the jump heights (in centimeters) for 12 international soccer players are given in the accompanying table. The correlation coefficient, rounded to three decimal places, is r=0.707. At & = 0.05, is there enough evidence to conclude that there is a significant linear correlation between the variables? Click the icon to view the soccer player data. Determine the null and alternative hypotheses. Ho:p = 0 Ha:p # 0 Determine the critical value(s). to = (Round to three decimal places as needed. Use a comma to separate answers as needed.)You wish to determine if there is a positive linear correlation between the age of a driver and the number of driver deaths. The following table represents the age of a driver and the number of driver deaths per 100,000. Use a significance level of 0.05 and round all values to 4 decimal places. Driver Age Number of Driver Deaths per 100,000 77 28 47 31 74 32 65 32 26 20 79 36 52 29 Ho: ρ = 0Ha: ρ > 0 Find the Linear Correlation Coefficient r = Find the p-value p-value =
- See the attached image for the introduction. Question: Fill in a blank ANOVA table.quare for this model? C12. Using Monitoring the Future 2017 data, we examine whether a relationship exists between the race/ethnicity of a student and how the student rates the importance of being a community leader. IMPLDRCOMUNTY is measured on an ordinal scale: I = not important, 2 = somewhat important, 3 = quite important, and 4 = extra important. Analysis of variance results are presented. %3D %3D %3D Descriptives 171A007H:IMP LDR COMUNTY 95% Confidence Interval for Mean Std. Deviation Mean Std. Error Lower Bound Upper Bound Minimum Maximum BLACK:(1) 276 2.91 .996 .060 2.79 3.03 1 WHITE:(2) 1041 2.51 .969 .030 2.45 2.57 1 4 HISPANIC:(3) 380 2.53 1.005 .052 2.43 2.64 4 Total 1697 2.58 .991 .024 2.53 2.63 4 ANOVA 171A007H:IMP LDR COMUNTY Sum of df Mean Square Sig. Squares 17.918 18.605 .00 Between Groups 35.836 1694 .963 Within Groups 1631.435 1667.270 1696 Total a. Set alpha at .05. What do you conclude about the relationship between student race/ ethnicity and the importance of…Listed below are paired data consisting of amounts spent on advertising (in millions of dollars) and the profits (in millions of dollars). Determine if there is significant linear correlation between advertising cost and profit . Use a significance level of 0.10 and round all values to 4 decimal places. Advertising Cost Profit 3 23 4 23 5 22 6 26 7 25 8 25 9 25 10 30 11 31 12 31 Ho: ρ = 0Ha: ρ ≠ 0 Find the Linear Correlation Coefficient r = Find the p-value p-value =
- please answer blank questions only and or ones with a red x next to them.The systolic blood pressure of individuals is thought to be related to both age and weight. Let the systolic blood pressure, age, and weight be represented by the variables x1, x2, and x3, respectively. Suppose that Minitab was used to generate the following descriptive statistics, correlations, and regression analysis for a random sample of 15 individuals. Descriptive Statistics Variable N Mean Median TrMean StDev SE Mean x1 15 158.42 158.72 158.42 3.127 0.807388 x2 15 65.95 66.45 65.95 1.091 0.281695 x3 15 187.23 186.63 187.23 4.171 1.076948 Variable Minimum Maximum Q1 Q3 x1 124 174 135.828 166.400 x2 41 80 47.088 77.579 x3 124 244 142.885 223.525 Correlations (Pearson) x1 x2 x2 0.829 x3 0.860 0.661 Regression Analysis The regression equation is x1 = 0.837 + 1.120x2 + 0.928x3 Predictor Coef StDev T P…You wish to determine if there is a negative linear correlation between the age of a driver and the number of driver deaths. The following table represents the age of a driver and the number of driver deaths per 100,000. Use a significance level of 0.01 and round all values to 4 decimal places. Driver Age Number of Driver Deaths per 100,000 31 23 60 27 33 18 64 36 72 31 65 31 Ho: ρ = 0Ha: ρ < 0 Find the Linear Correlation Coefficient r = Find the p-value p-value = The p-value is Less than (or equal to) αα Greater than αα The p-value leads to a decision to Reject Ho Accept Ho Do Not Reject Ho The conclusion is There is insufficient evidence to make a conclusion about the linear correlation between driver age and number of driver deaths. There is a significant linear correlation between driver age and number of driver deaths. There is a significant positive linear correlation between driver age and number of driver deaths. There is a…
- You wish to determine if there is a positive linear correlation between the age of a driver and the number of driver deaths. The following table represents the age of a driver and the number of driver deaths per 100,000. Use a significance level of 0.01 and round all values to 4 decimal places. Driver Age Number of Driver Deaths per 100,000 66 20 75 32 44 31 44 36 19 23 65 29 61 22 58 25 71 27 Ho: ρ = 0Ha: ρ > 0 Find the Linear Correlation Coefficient r = Find the p-value p-value =1. Show a One-Way ANOVA using the dataset found in the given excel (Sheet name: Smoking). Copy the result of the statistics and provide an interpretation of it. Description of Data: A research was conducted to quantify the effect of cigarette smoking on standard measures of lung function in patients with idiopathic pulmonary fibrosis. 2. Show a Two-Way ANOVA using the dataset found in the given excel (Sheet name: Trauma). Copy the result of the statistics and provide an interpretation of it. Description of Data: The research compares different combinations of four types of psychiatric treatment (A, B, C, and D) and six physical therapy programs (I, II, III, IV, V, and VI). •(NOTE: This is my one last remaining question. So, please answer the two given situations.)The data in the table to the right are based on the results of a survey comparing the commute time of adults to their score on a well-being test. Complete parts (a) through (d) below. Click the icon to view the critical values for the correlation coefficient. Score 70+ r= 60- (a) Which variable is likely the explanatory variable and which is the response variable? A. The explanatory variable is commute time and the response variable is the well-being score because commute time affects the well-being score. B. The explanatory variable is commute time and the response variable is the well-being score because well-being score affects the commute time score. C. The explanatory variable is the well-being score and the response variable is commute time because commute time affects the well-being score. D. The explanatory variable is the well-being score and the response variable is commute time because well-being score affects the commute time. (b) Draw a scatter diagram of the data. Which…