BA 253: Linear Regression



BA 253: Linear Regression

A) Are advertising and sales related? Assume that the manager of a store has had five different

advertising campaigns and has kept track of the sales volume associated with each campaign.

|Ad |Sales |

|$3,000 |$14,000 |

|$5,000 |$26,000 |

|$8,000 |$29,000 |

|$10,000 |$46,000 |

|$13,000 |$48,000 |

a) Graph the data. Do they appear linear?

b) Calculate the linear regression equation.

c) Interpret the slope of the linear regression line.

d) Predict sales if the manager spends $9000 on ads.

e) Determine the coefficients of determination and

correlation, and interpret them.

f) At ( = 5%, test for the existence of correlation.

Do a) through f) on calculator, then on MS Excel

B) The data below represent the demand for a product over the past 5 months.

|Month |Demand |

|1 |187 |

|2 |167 |

|3 |171 |

|4 |155 |

|5 |144 |

a) Graph the data and the linear regression line.

b) Determine the linear regression equation.

c) Interpret the slope.

d) Predict demand in weeks 6, 7, and 8.

e) Determine r and r2, and interpret them.

f) At α = 5%, test for the existence of correlation.

BA 253: Linear Regression

A) Are advertising and sales related? Assume that the manager of a store has had five different

advertising campaigns and has kept track of the sales volume associated with each campaign.

|Ad |Sales |

|$3,000 |$14,000 |

|$5,000 |$26,000 |

|$8,000 |$29,000 |

|$10,000 |$46,000 |

|$13,000 |$48,000 |

a) Graph the data. Do they appear linear?

b) Calculate the linear regression equation.

c) Interpret the slope of the linear regression line.

d) Predict sales if the manager spends $9000 on ads.

e) Determine the coefficients of determination and

correlation, and interpret them.

f) At ( = 5%, test for the existence of correlation.

Do a) through f) on calculator, then on MS Excel

B) The data below represent the demand for a product over the past 5 months.

|Month |Demand |

|1 |187 |

|2 |167 |

|3 |171 |

|4 |155 |

|5 |144 |

a) Graph the data and the linear regression line.

b) Determine the linear regression equation.

c) Interpret the slope.

d) Predict demand in weeks 6, 7, and 8.

e) Determine r and r2, and interpret them.

f) At α = 5%, test for the existence of correlation.

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