Longest Commute to Work

I am willing to pay $15 for help on my week 5-8 DQ and assignments. 

Week 7 DQ

The text states that "Significance of the linear correlation coefficient does not mean that you have established a cause and effect relationship." Explain that statement in your own words.

Week 7 Assignment

Question 1

To compare commuting times in various locations, independent random samples were obtained from the six cities presented in the “Longest Commute to Work” graphic on page 255 in your textbook. The samples were from workers who commute to work during the 8:00 a.m. rush hour. One-way Travel to Work in Minutes

Atlanta	Boston	Dallas	Philadelphia	Seattle	St. Louis
29	18	42	29	30	15
21	37	25	20	23	24
20	27	26	33	31	42
15	25	32	37	39	23
37	32	20	42	14	33
26	34	26			18
	48	35

• Construct a graphic representation of the data using six sid-by-side dotplots.
• Visually estimate the mean commute time for each city and locate it with an X.
• Does it appear that different citites have different effects on the average amount of time spent by workers who commute to work during the 8:00 a.m. rush hour? Explain.
• Does it visually appear that different cities have different effects on the variation in the amount of time spent by workers wo commute to work during the 8:00 a.m. rush hour? Explain.

Part 2

• Calculate the mean commute time for each city depicted.
• Does there seem to be a difference among the mean one-way commute times for these six cities?
• Calculate the standard deviation for each city’s commute time.
• Does there seem to be a difference among the standard deviations between the one-way commute times for these six cities?

Part 3

• Construct the 95% confidence interval for the mean commute time for Atlanta and Boston.
• Based on the confidence intervals found does it appear that the mean commute time is the same or different for these two cities (Atlanta and Boston). Explain
• Construct the 95% confidence interval for the mean commute time for Dallas.
• Based on the confidence intervals found in (Atlanta and Boston) and Dallas does it appear that the mean commute time is the same or different for Boston and dalls? Explain.
• Based on the confidence levels found in (Atlanta and Boston) and (Dallas) does it appear that the mean commute time is the same or different for the set of three cities, Atlanta, Boston, and Dallas? Explain
• How doe your confidence intervals compare to the intervals given for Atlant, Boston, and Dallas in “Longest Commute to Work” on page 255?

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Question 2

Interstate 90 is the longest of the east-west U.S. interstate highways with its 3,112 miles stretching from Boston, MA at I-93 on the eastern end to Seattle WA at the Kingdome on the western end. It travels across 13 northern states; the number of miles and number of intersections in each of those states is listed below.

State	No. of Inter	Miles
WA	57	298
ID	15	73
MT	83	558
WY	23	207
SD	61	412
MN	52	275
WI	40	188
IL	19	103
IN	21	157
OH	40	244
PA	14	47
NY	48	391
MA	18	159

• Construct a scatter diagram of the data.
• Find the equation for the line of best fit using x= miles and y=intersections.
• Using the equation found in part (b), estimate the average number of intersections per mile along I-90.
• Find a 95% confidence interval for β₁.
• Explain the meaning of the interval found in part d.

Week 5 Assignment (just need the first question answered)

Question 1

Using the telephone numbers listed in your local directory as your population, randomly obtain 20 samples of size 3. From each telephone number identified as a source, take the fourth, fifth, and sixth digits.

• Calculate the mean of the 20 samples
• Draw a histogram showing the 20 sample means. (Use classes -0.5 to 0.5, 0.5 to 1.5, 1.5 to 2.5 and so on).
• Describe the distribution of the x-bars that you see in part b (shape of distribution, center, and the amount of dispersion).
• Draw 20 more samples and add the 20 new x-bars to the histogram in part b. Describe the distribution that seems to be developing.

Use the empirical rule to test for normality. See the sampling distribution of sample means and the central limit theorem develop from your own data!

Question 2.

Sample statistics d = A – B = 3.75   n= 8     std deviation = 5.726

Step 1. The mean difference in weight gain for pigs fed ration A as compared to those fed ration B

Step 2.

a.       Normally indicated

b.      T

c.       Confidence interval 1 – alfa = 0.95

Step 3.  n=8   d=3.75  std deviation = 5.726

Step 4;

a.       Alfa/2 = 0.05/2 = 0.025, find degree of freedom df = n-1, then find t-distribution on page 335

b.      E = t(df, 0.025) * (sd/square root of n) = ?

c.       d+/- E = ?

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