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Part A: Analysis of traffic data                     

 In this section you will use the data you collected in Assignment 1.

Car Size (m^3)

Body

Year

Year

9.941

Small Cars

2003

Less than 2005

10.251

Small Cars

1996

Less than 2005

10.699

Small Cars

2012

Greater than 2005

9.139

Medium Cars

1972

Less than 2005

10.426

Medium Cars

1986

Less than 2005

11.304

Medium Cars

2001

Less than 2005

12.255

Medium Cars

2007

Greater than 2005

12.332

Medium Cars

2007

Greater than 2005

13.305

Large Cars

2004

Less than 2005

13.387

Large Cars

2004

Less than 2005

13.955

Large Cars

2004

Less than 2005

13.402

Large Cars

2011

Greater than 2005

13.470

Large Cars

2011

Greater than 2005

13.484

Large Cars

2010

Greater than 2005

14.618

Luxury Cars

2010

Greater than 2005

14.987

Luxury Cars

2010

Greater than 2005

13.814

Luxury Cars

2002

Less than 2005

14.278

Luxury Cars

2002

Less than 2005

 1. Comparing two means:

a) Confidence interval for difference between means

 (i) Use Minitab to construct a 95% Confidence Interval for the difference between the means of your numeric variable for the different levels of your 2-level categorical variable.                                                                                                               

(ii) Interpret your confidence interval in context (remember units).

(iii) Use your confidence interval to draw a conclusion about the difference (if any) between the two levels of your categorical variable.

 b) Two-tailed hypothesis test for the difference between two means

(i) State the null and alternative hypotheses (in words and symbols) for testing if there is a significant difference between the means of your numeric variable for the different levels of your 2-level categorical variable.

(ii) Use Minitab to carry out the test. State the test statistic and corresponding p-value for these hypotheses.

(iii) Explain whether you have evidence for or against the null hypothesis.

(iv) State your conclusion in a form that a non-statistician would understand.

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