1. Briefly explain the three factors that contribute to genetic variability.
   1. Independent assortment
   2. Crossover of homologues
   3. Random fertilization
2. Briefly describe the following. Provide an example for each.
   1. Dominant-recessive inheritance
   2. Incomplete dominance inheritance
   3. Multiple-allele inheritance
   4. Sex-linked inheritance
   5. Polygene inheritance
   6. Extranuclear (mitochondrial) inheritance (not really a pattern
3. What role, if any, do environmental factors play in gene expression?
4. What is genetic screening? Why do they determine pedigrees?
5. What do we mean by the following terms:
   1. Homozygous trait
   2. Heterozygous trait
   3. Dominant gene
   4. Recessive gene

One of the major measures of quality of services provided by any organization is the speed with which it responds to customer complaints. A large family- held department store selling furniture and flooring, including carpet, had undergone a major expansion in the past several years. In particular, the flooring department had expanded from 2 installation crews. The store had the business objective of improving its response to complaints. The variable of interests was defined as the number of days between when the complaint was made and when it was resolved. Data were collected from 50 complaints that were made in the past year. These data, stored in furniture, are:

54 5 35 137 31 27 152 2 123 81 74 27

11 19 126 110 110 29 61 35 94 31 26 5

12 4 165 32 29 28 29 26 25 1 14 13

13 10 5 27 4 52 30 22 36 26 20 23

33 68

a) The installation supervisor claims that the mean number of days between the receipt of a complaint and the resolution of the complaint is 20 days. At the 0.05 level of significance, is there evidence that the claim is not true?

b) What assumption about the population distribution is needed in order to conduct the t-test in (a)?

c) construct a boxplot or a normal probability plot to evaluate the assumption made in (b)?

d) Do you think that the assumption needed in order to conduct the t-test in (a) is valid? Explain.

Question 2:

In this part, we will use t-procedures. t-procedures are both confidence intervals and hypothesis tests that

use a t distribution. They are called t-procedures because they rely on a t-test statistic and/or a t-critical

value, so we only need to know the results of a sample in order to perform these procedures for a population

You will use the data file TempSample00-18.

(THIS is Temp sample data)

YEAR,Month,High Temperature

2000,Jan,45

2000,Jan,48

2001,Jan,49

2003,Jan,62

2003,Jan,53

2004,Jan,42

2004,Jan,47

2005,Jan,40

2005,Jan,47

2006,Jan,48

2006,Jan,47

2007,Jan,51

2007,Jan,34

2007,Jan,47

2009,Jan,50

2011,Jan,35

2012,Jan,44

2013,Jan,38

2013,Jan,53

2013,Jan,42

2014,Jan,58

2014,Jan,47

2014,Jan,44

2015,Jan,52

2016,Jan,44

2017,Jan,49

2018,Jan,54

2000,Feb,48

2001,Feb,47

2004,Feb,47

2007,Feb,51

2008,Feb,51

2008,Feb,55

2011,Feb,45

2014,Feb,37

2014,Feb,54

2014,Feb,58

2015,Feb,54

2017,Feb,52

2017,Feb,44

2017,Feb,45

This includes an SRS of daily temperature highs from January and February from the years 2000-2018

(i.e. “recent” highs). The distribution of “recent” daily high temperatures is approximately Normal.

A.

1) Describe the intended population?

2) Describe the sample?

3) Describe the variable of interest?

4) Describe the parameter of interest (in context)?

5) Describe the statistic of interest (in context)? Give a numerical value along with your description.

Round to two decimal places.

B.

1) Check that the conditions for using t-procedures are satisfied. If they are not, discuss whether or not it is reasonable to use t-procedures.

C.

1) What degrees of freedom are needed?

2) What critical value is used to compute a 95% confidence interval?

3) Give the 95% confidence interval. Round to two decimal places.

4) Interpret your 95% confidence interval.

D.

1) Perform a hypothesis test for α = .01. Be sure to interpret your p-value in context.

E.

1) Based on your work in Part B, what would you say about the daily high temperature for “recent” years compared to “historical” years?

Question 2:

In this part, we will use t-procedures. t-procedures are both confidence intervals and hypothesis tests that

use a t distribution. They are called t-procedures because they rely on a t-test statistic and/or a t-critical

value, so we only need to know the results of a sample in order to perform these procedures for a population

You will use the data file TempSample00-18.

(THIS is Temp sample data)

YEAR,Month,High Temperature

2000,Jan,45

2000,Jan,48

2001,Jan,49

2003,Jan,62

2003,Jan,53

2004,Jan,42

2004,Jan,47

2005,Jan,40

2005,Jan,47

2006,Jan,48

2006,Jan,47

2007,Jan,51

2007,Jan,34

2007,Jan,47

2009,Jan,50

2011,Jan,35

2012,Jan,44

2013,Jan,38

2013,Jan,53

2013,Jan,42

2014,Jan,58

2014,Jan,47

2014,Jan,44

2015,Jan,52

2016,Jan,44

2017,Jan,49

2018,Jan,54

2000,Feb,48

2001,Feb,47

2004,Feb,47

2007,Feb,51

2008,Feb,51

2008,Feb,55

2011,Feb,45

2014,Feb,37

2014,Feb,54

2014,Feb,58

2015,Feb,54

2017,Feb,52

2017,Feb,44

2017,Feb,45

This includes an SRS of daily temperature highs from January and February from the years 2000-2018

(i.e. “recent” highs). The distribution of “recent” daily high temperatures is approximately Normal.

A.

1) Describe the intended population?

2) Describe the sample?

3) Describe the variable of interest?

4) Describe the parameter of interest (in context)?

5) Describe the statistic of interest (in context)? Give a numerical value along with your description.

Round to two decimal places.

B.

1) Check that the conditions for using t-procedures are satisfied. If they are not, discuss whether or not it is reasonable to use t-procedures.

C.

1) What degrees of freedom are needed?

2) What critical value is used to compute a 95% confidence interval?

3) Give the 95% confidence interval. Round to two decimal places.

4) Interpret your 95% confidence interval.

D.

1) Perform a hypothesis test for α = .01. Be sure to interpret your p-value in context.

E.

1) Based on your work in Part B, what would you say about the daily high temperature for “recent” years compared to “historical” years?

Three experiments investigating the relation between need for cognitive closure and persuasion were performed. Part of the study involved administering a "need for closure scale" to a group of students enrolled in an introductory psychology course. The "need for closure scale" has scores ranging from 101 to 201. For the 74 students in the highest quartile of the distribution, the mean score was x = 177.30. Assume a population standard deviation of σ = 7.61. These students were all classified as high on their need for closure. Assume that the 74 students represent a random sample of all students who are classified as high on their need for closure. Find a 95% confidence interval for the population mean score μ on the "need for closure scale" for all students with a high need for closure. (Round your answers to two decimal places.)

Wal-Mart is the second-largest retailer in the world. The data file (Wal-Mart Revenue 2004-2009 data.xlsx) is posted below the case study two file, and it holds monthly data on Wal-Mart’s revenue, along with several possibly related economic variables.

1. Develop a multiple linear regression model to predict Wal-Mart's revenue, using CPI, Personal Consumption, and Retail Sales Index as the independent variables. You also need to create residual plots and scatter plots by selecting residual plots box and line fit plots box under “Residuals”. Note: Those plots are for the individual independent variables.
2. To generate the residual plot for the entire model, you need to follow the instruction below. Check the Residuals box under “Residuals” and Excel will generate predicted values and residuals at the bottom of the output for the multiple regression model. Then, highlight these two output values to create the residual plot by Excel’s scatter chart (Insert tab > Charts > Scatter chart). Comment on what you see on the plot. Note: This residual plot is for the entire model.
3. Does it seem that Wal-Mart’s revenue is closely related to the general state of the economy? Use all the plots and statistical criteria on the Regression Analysis output generated by Excel to explain it.

Identify and delete those five cases (rows) corresponding to December revenue. Then, use the new data set (without the December data) to complete the following problems.

4. Develop a multiple linear regression model to predict Wal-Mart's revenue, using CPI, Personal Consumption, and Retail Sales Index as the independent variables. You also need to create residual plots and scatter plots by selecting residual plots box and line fit plots box under “Residuals”. Note: Those plots are for the individual independent variables.
5. Check the Residuals box under “Residuals” and Excel will generate predicted values and residuals at the bottom of the output for the multiple regression model. Then, highlight these two output values to create the residual plot by Excel’s scatter chart (Insert tab > Charts > Scatter chart). Comment on what you see on the plot. Note: This residual plot is for the entire model.
6. Does it seem that Wal-Mart’s revenue is closely related to the general state of the economy? Use all the plots and statistical criteria on the Regression Analysis output generated by Excel to explain it.
7. Compare these two multiple regression models, and decide which of these two models is better? Use R-square values, adjusted R-square values, Significance F values, p-values, scatter plots and residual plots to explain your answer.

A cable company offers two basic packages: sports and kids, and a combined package. There are three different types of users: parents, sports fans, and generalists. Assume that the cable company cannot discriminate among the three groups and must charge all customers the same price. The following table shows the maximum price that each type of consumer is willing to pay for each package. Sports Package Kids Package Parents 10 50 Sports fans 50 10 Generalists 40 40

If the cable company sells the packages separately, how much price should it charge for each package? What will be total revenue? What will happen if this price is slightly raised?

b. Rather than raising the single package price to increase revenue, suppose now the firm opts to offer mixed bundling where the customers can buy either a single package or a bundled package. Show that the cable company will earn a higher revenue with mixed bundling than the single pricing method in part a.

The author thou questioned Fowler’s case since the court drew analysis based on their unsuccessful attempt to obtain Florida driver’s license, register the car, register as Florida voter and their intention of being Florida residence as from January 20, 2006. It failed to attribute the sale of stock on February 3, 2006, where Mrs. Fowler served as Assistant Secretary for three years in North Carolina. The charitable contributions after the sale of the business in 2006 and during that year, the taxpayers spent most of 2006 - 2007 days in North Carolina before finalizing the proposal. The court and IRS'S brings out the contradiction in the governing principles of determining an individual's domicile. Since thou, the Fowlers changed their address to Florida they continued using certain correspondence and billing and bank statements from North Carolina. The insurance policy that they purchased on their North Carolina home for a period of July 31, 2006 to July 31, 2007 had a stipulated location that dwelling is not seasonal or secondary. The court failed to consider Fowlers' behavior prior to January 20,2006 and emphasized on a single observed event, hence ignoring taxpayers’ subsequent conduct.

QUESTION: DO YOU AGREE WITH THE ABOVE STATEMENT? EXPLAIN

February 1^st transaction is completed as an example:  Only include the letter of the account not the account name.

27.            $__________If January 31st cash was $10,000, what is the cash balance at the end of the day on 2/28?