Question

In: Statistics and Probability

The following data represents the heights of the old faithful geyser eruptions, the durations of the...

  1. The following data represents the heights of the old faithful geyser eruptions, the durations of the eruption and the interval between eruptions. The data is attached and an excel file is also included on canvas. The data is arranged in duration, interval and height

a) Use the paired data for durations and intervals after eruptions of the geyser. Is there significant linear correlation at the 0.05 significance level suggesting interval after an eruption is related to duration (use the r value approach)?

b) Use the paired data for heights of eruptions and intervals after eruptions of the old faithful geyser. Is there significant linear correlation suggesting interval is related to height? Use a 0.05 significance level and again use r value approach.

c) Using the paired data for durations (x) and intervals (y) after eruptions of the geyser, find a linear regression equation. What is the best predicted time before the next eruption if the previous eruption lasted 210 seconds?

Duration

Interval

Height

Duration

Interval

Height

240

86

140

120

57

139

237

86

154

267

100

110

122

62

140

103

62

140

267

104

140

270

87

135

113

62

160

241

70

140

258

95

140

239

88

135

232

79

150

233

82

140

105

62

150

238

83

139

276

94

160

102

56

100

248

79

155

271

81

105

243

86

125

127

74

130

241

85

136

275

102

135

214

86

140

140

61

131

114

58

155

264

83

135

272

89

130

134

73

153

227

79

125

268

97

155

237

83

125

124

67

140

238

82

139

270

90

150

203

84

125

249

84

153

270

82

140

237

82

120

218

78

140

235

81

138

226

91

135

228

78

135

250

89

141

265

89

145

245

79

140

120

69

130

241

79

150

275

98

136

Solutions

Expert Solution

  1. The following data represents the heights of the old faithful geyser eruptions, the durations of the eruption and the interval between eruptions. The data is attached and an excel file is also included on canvas. The data is arranged in duration, interval and height

a) Use the paired data for durations and intervals after eruptions of the geyser. Is there significant linear correlation at the 0.05 significance level suggesting interval after an eruption is related to duration (use the r value approach)?

Calculated r=0.8701 which is > 0.279 the critical r at 0.05 level of significance. r is significant.

There is a significant linear correlation at the 0.05 significance level suggesting interval after an eruption is related to duration.

b) Use the paired data for heights of eruptions and intervals after eruptions of the old faithful geyser. Is there significant linear correlation suggesting interval is related to height? Use a 0.05 significance level and again use r value approach.

Calculated r=0.-0.0098

|r| = 0.0098 which is < 0.279 the critical r at 0.05 level of significance. r is not significant.

There is no significant linear correlation at the 0.05 significance level suggesting interval is related to height.

c) Using the paired data for durations (x) and intervals (y) after eruptions of the geyser, find a linear regression equation. What is the best predicted time before the next eruption if the previous eruption lasted 210 seconds?

The estimated regression line is

Interval (y) =41.945 +0.179 * durations (x)

When duration = 210,

Predicted Interval (y) =41.945 +0.179 * 210

=79.47

Excel Addon Megastat used.

Menu used: correlation/Regression ---- Correlation Matrix

Correlation Matrix

Duration

Interval

Height

Duration

1.0000

0.8701

-0.0187

Interval

0.8701

1.0000

-0.0098

Height

-0.0187

-0.0098

1.0000

50

sample size

± .279

critical value .05 (two-tail)

± .361

critical value .01 (two-tail)

Menu used: correlation/Regression ---- Regression Analysis.

Regression Analysis

0.757

n

50

r

0.870

k

1

Std. Error of Estimate

5.964

Dep. Var.

Interval

Regression output

confidence interval

variables

coefficients

std. error

   t (df=48)

p-value

95% lower

95% upper

Intercept

a =

41.945

Duration

b =

0.179

0.015

12.231

2.33E-16

0.149

0.208

ANOVA table

Source

SS

df

MS

F

p-value

Regression

5,321.685

1  

5,321.685

149.60

2.33E-16

Residual

1,707.535

48  

35.574

Total

7,029.220

49  

Predicted values for: Interval

95% Confidence Interval

95% Prediction Interval

Duration

Predicted

lower

upper

lower

upper

Leverage

210

79.47

77.77

81.18

67.36

91.59

0.020


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