Reference no: EM131990494

Question 1

Missy Walters owns a mail-order business specializing in clothing, linens, and furniture for children. She is considering offering her customers a discount on shipping charges for furniture based on the dollar-amount of the furniture order. Before Missy decides the discount policy, she needs a better understanding of the dollar-amount distribution of the furniture orders she receives.

Missy had an assistant randomly select 50 recent orders that included furniture. The assistant recorded the value, to the nearest dollar, of the furniture portion of each order. The data collected is listed below (data set also provided in accompanying MS Excel file).

136	281	226	123	178	445	231	389	196	175
211	162	212	241	182	290	434	167	246	338
194	242	368	258	323	196	183	209	198	212
277	348	173	409	264	237	490	222	472	248
231	154	166	214	311	141	159	362	189	260

a. Prepare a frequency distribution, relative frequency distribution, and percent frequency distribution for the data set using a class width of $50.

b. Construct a histogram showing the percent frequency distribution of the furniture- order values in the sample. Comment on the shape of the distribution.

c. Given the shape of the distribution in part b, what measure of location would be most appropriate for this data set?

Question 2

Shown below is a portion of a computer output for a regression analysis relating Y (demand) and X (unit price).

ANOVA
	df	SS
Regression	1	5048.818
Residual	46	3132.661
Total	47	8181.479
	Coefficients	Standard Error
Intercept	80.390	3.102
X	-2.137	0.248

a. Determine whether or not demand and unit price are related. Use α = 0.05.

b. Compute the coefficient of determination and fully interpret its meaning.
Be very specific.

c. Compute the coefficient of correlation and explain the relationship between demand and unit price.

Question 3

The following are the results from a completely randomized design consisting of 3 treatments.

Source of Variation	Sum of Squares	Degrees of Freedom	Mean Square	F
Between Treatments	390.58
Within Treatments (Error)	158.40
Total	548.98	23

Using α = .05, test to see if there is a significant difference among the means of the three populations. The sample sizes for the three treatments are equal.

Question 4

In order to determine whether or not the number of mobile phones sold per day (y) is related to price (x1 in $1,000), and the number of advertising spots (x2), data were gathered for 7 days. Part of the Excel output is shown below.

ANOVA

df                   SS                        MS              F

Regression                            40.700

Residual                                1.016

Coefficients Standard Error

Intercept          0.8051

x₁                     0.4977           0.4617

x₂                     0.4733           0.0387

a. Develop an estimated regression equation relating y to x₁ and x₂.

b. At α = 0.05, test to determine if the estimated equation developed in Part a represents a significant relationship between all the independent variables and the dependent variable.

c. At α = 0.05, test to see if β₁ and β₂ is significantly different from zero.

d. Interpret slope coefficient for X₂.

e. If the company charges $20,000 for each phone and uses 10 advertising spots, how many mobile phones would you expect them to sell in a day?

Attachment:- Data set.xlsx