# Linear Regression and Statistics

**Topics:**Regression analysis, Household income in the United States, Linear regression

**Pages:**4 (930 words)

**Published:**September 18, 2010

ANOVA & Least Squares

Tyrone Sewell

Statistics, MAT 201, Module V-CA5

Alfred Basta

December 20, 2009

Statistics

ANOVA & Least Squares

Look at the data below for the income levels and prices paid for cars for ten people: | Annual Income Level |Amount Spent on Car |

|38,000 |12,000 |

|40,000 |16,000 |

|117,000 |41,000 |

|17,000 |3,500 |

|23,000 |6,500 |

|79,000 |21,000 |

|33,000 |5,000 |

|66,000 |8,000 |

|15,000 |1,500 |

|52,000 |6,000 |

Answer the following questions:

A. What kind of correlation do you expect to find between annual income and amount spent on car? Will it be positive or negative? Will it be a strong relationship? Base your answer on your personal guess as well as by looking through the data.

The annual income and amount of money spent on a car correlates that generally the greater the sum of income the larger portion of money spent on a car. The middle/low to middle income in datas spent the most with percentages ranging from the low 21% to 40%. The middle/high income percentages took a much smaller percentage rate at 12% and 35%. While the low income percentages represented only 10% of their incomes spent toward a new car purchase. The trend makes the graph ascend on both sides of the linear regression line. When the incomes of the consumer increase the sales for cars also rises presenting a positive result. Therefore, as long as the incomes continue to grow the relationship to car sales will also trend to the right in an upward, positive motion. B. What is the direction of causality in this relationship - i.e. does having a more expensive car...

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