Using R Software
library(readxl)
Data<-read_excel("your pc data path
where you store data.xlsx")
Reg=lm(Y~X,data=Data)
Reg
summary(Reg)
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1. A study found that age and blood pressure are correlated. The data is shown below....
2. A study of the relationship between age and blood pressure yielded the following data Blood Pressure (Y 126 131 161 128 1489 140 148 Test using a significance level of 5% whether there is an increasing linear relationship Age(X) 23 27 45 3 536 37 37 a. between age and blood pressure. Parameter: A- slope of regression line for blood pressure vs.age. Hypotheses: Test Statistic: t.A-A d.f- with the same variance. Rejection Region: Calculated Test: Conclusion P-value. b. Find...
A 10-year study conducted by the American Heart Association provided data on how age, blood pressure, and smoking relate to the risk of strokes. Data from a portion of this study follow. Risk is interpreted as the probability (times 100) that a person will have a stroke over the next 10-year period. For the smoker variable, 1 indicates a smoker and 0 indicates a nonsmoker. Risk Age Blood Pressure Smoker 14 58 201 0 23 82 98 1 25 74...
topic: model selection on applied linear regression
Exercise 5.5.10 Perform model selection for the blood pressure data in Table 3.1 using Ri and stepwise selection algorithm. Compare the results with all possible subsets regression. 47 3.8 Exercises Age Weight Pulse Blood pressure 21 7 88 24 56 70 25 65 72 28 53 60 32 67 60 35 80 70 7 57 68 38 58 64 39 68 75 160 135 140 118 134 60 67 1 64 8 42...
A 10-year study conducted by the American Heart Association provided data on how age, blood pressure, and smoking relate to the risk of strokes. Assume the following data are from a portion of this study. Risk is interpreted as the probability (times 100) that the patient will have a stroke over the next 10-year period. For the smoking variable, define a dummy variable with 1 indicating a smoker and 0 indicating a nonsmoker. (See the Stroke file in the document...
A 10-year study conducted by the American Heart Association provided data on how age, blood pressure, and smoking relate to the risk of strokes. Data from a portion of this study follow. Risk is interpreted as the probability (times 100) that a person will have a stroke over the next 10-year period. For the smoker variable, 1 indicates a smoker and 0 indicates a nonsmoker Click on the datafile logo to reference the data. DATA file Risk Blood Pressure Smoker...
The systolic blood pressure of individuals is thought to be related to both age and weight. For a random sample of 11 men, the following data were obtained Weight (pounds) Systolic Blood pressue Age (years) 149 132 52 173 143 59 184 153 67 194 162 73 211 154 64 196 16B 74 220 137 54 188 61 188 159 65 207 128 46 167 166 72 217 (a) Generate summary statistics, including the mean and standard deviation of each...
Risk
Age
Blood Pressure
Smoker
10
59
220
1
33
67
129
0
14
68
170
0
59
63
198
0
30
65
173
0
52
74
172
1
9
77
159
0
28
73
173
0
32
68
117
1
20
80
209
1
40
62
176
1
41
82
110
0
25
67
151
1
56
55
191
0
36
61
208
1
32
61
112
1
26
78
125
0
28
75
129
0
18
90
184...
6. Of all people in one population, 21% have high blood pressure and 36% are overweight. In addition, 42% of people who are overweight also have high blood pressure. Let H represent the event that a person has high blood pressure, and O represent the event that a person is overweight. In each part of this question, you must first express each probability in terms of the events Hand O and justify any computation through the use of a formula....
The data show systolic and davol blood pressure of certain people. Find the regression equation letting the st is the predicted value does lo 69.0, which was the actual diastolic roading? Use agricance level of 0.05. reading bete independent variabile Find the best predicted distresu for a persona t g e 150 Diastolle Cok the loon to view the co 101 102 104 3 u es of the Pearson correlation coefficient 74 What is the regression equation? Y o und...
Consider the dataset in the proj2-3.txt file on BlackBoard. In this problem, focus is on high systolic blood pressure (sbp) and possible explanatory variables Body Mass Index (bmi), and scale (scl). Consider the linear regression model with response high SBP and scale as explana- tory variables. Explain the coefficients in the model? Explain the null hypotheses that the estimated slope equals 0? Write a summary of your findings. What is your conclusion? Residuals: Min 1Q Median 3Q Max -72.64 -27.55...