statistics

  1. State the general model of regression analysis
  2. Discuss the different types of regression
  3. Using the hypothetical data below:
  1. Run regression to determine how well can blood pressure (BP) be predicted from anxiety and weight combined?

ANXIETY

WEIGHT

BLOOD PRESSURE

7

90

137

10 

130

158

35

30

163

19

151

133

17

170

106

11

190

128

18

210

168

36

91

145

19

90

149

22

95

143

28

130

145

25

150

123

4

110

145

25

150

143

18

110

113

7

150

119

16

230

139

25

315

173

28

250

176

10

210

178

34

271

174

22

250

176

17

230

156

16

185

144

 

  1. What is the null hypothesis for the overall multiple regression?
  2. Run a regression analysis to predict blood pressure from weight and anxiety.
  3. How much variance in blood pressure is uniquely explained by each of these two predictor variables?
  4. What is multicollinearity in multiple regression, and why is it a problem?
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1 Answer

"regreshun analysis"....find a strate line best fit tu data

want tu min the sum av squares av distans from the line tu all points

normally hav y=f(x), so yu get the x-distans av all points

Jenral solv...yu gotta get invers av matrix [n bi n], n=number points
by

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