An executive at a telecommunications company is interested in the relationship between an individual’s income and their mobile phone usage. He surveyed 10 mobile-phone users and recorded their annual incomes and time (in minutes) spent each week making national direct calls. The data is presented in sequence according to gross annual income. Â
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Individual Annual income (000) National direct calls (minutes) 1 23 69 2 29 95 3 35 118 4 42 136 5 46 125 6 50 138 7 64 166 8 66 184 9 76 170 10 78 225Â
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a. Construct a scatter plot of the data above. (3 marks)Â Â
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b. Develop a least squares regression line to predict the direct calls in minutes based on annual income. (10 marks)Â Â
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c. What would be the predicted duration of direct call in minutes for an income of $48000? (3 marks)Â
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d. What is the error value for an income of $76000? (4 marks)Â
a) Scatter plot:
b) Regression analysis:
Regression equation:
"y \n\u2032\n =6776.14685X+1529.3779\ufeff"
c) When income is $43000, the predicted direct calls:
Using the regression equation:
"\ufeffy\u2032=6776.14685X+1529.3779\ufeff \\\\X = \\$43000\\\\\ufeffY \n\u2032\n =6776.14685\\times43000+1529.37879\ufeff \\\\\ufeffY \n\u2032\n =277185843.92879\ufeff"
d) Error formula:"\ufeff\ufeffS \ne\n\u200b\n =\u2211e \ni\n2\n\u200b\n =\u2211(Y\u2212Y \n\u2032\n ) \n2\n \ufeff"
Y' when X = $76000"\ufeffY \n\u2032\n =6776.14685\u221776000+1529.37879\ufeff \\\\\ufeffY \n\u2032\n =514988689.97879\ufeff \\\\\ufeff\u2211e \n2\n =(45574.3333\u2212514988689.97879) \n2\n =(\u2212277140269.59549) \n2\n \\\\=7.68067290E+16"
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