Change in Estimate versus Error Correction Facts: Your company, PlumbAll, provides routine and quick response plumbing services to a range of corporate customers. Customers are expected to pay on the first of each month, in advance of receiving services. One of your customers is a private school that has been a longtime customer. The customer has not paid for the last four months of services (September–December 20X1); nevertheless, to maintain a positive relationship, your company continued to provide services during that time. Your company ceased providing services in January 20X2 and found out in that same month that the school filed for bankruptcy in August. You now believe that the collection of the missed payments is extremely unlikely. Your company has already issued financial statements to lenders (for the period ending 12/31/X1) that reflected revenue and a corresponding account receivable related to this customer of $11,000 per month for services provided to this customer. Those financial statements also reflected the company’s standard allowance (reserve) amount on receivables of 3% of sales. In total, your company’s average monthly sales amount to $300,000.

Required:

1. Evaluate whether receipt of this information indicates you have a change in estimate or whether the customer’s bankruptcy results in this event being considered an error in previously issued financial statements.

2. Describe the accounting treatment required by the Codification for each alternative. Support your explanations with draft journal entries.

3. Briefly state which treatment appears to be more appropriate given the circumstances, describing any assumptions you made in concluding.

For the data in the Excel file Education and Income, find 95% confidence intervals for the mean annual income of males and the mean annual income of females. Can you conclude that the mean income of one group is larger than the other?

2. “Question2_Dataset.xlsx” contains the following data for several underdeveloped countries:

• Infant mortality rate
• Adult literacy rate
• Percentage of students finishing primary school
• Per capita GNP
  1. Use this data to develop an equation that can be used to predict infant mortality.
  2. Are there any outliers in this set of data?
  3. Interpret the coefficients in your equation. (What does each coefficient number mean?)
  4. Within what value should 95% of your predictions be infant mortality be accurate?

Miranda, a 26 year old Caucasian woman, has come in for an evaluation. She reports a history of sexual problems and is concerned about whether there is something physically wrong with her. She has been engaged for 2 years and has not yet had intercourse with her partner, but has noticed when they are physically close with one another, she doesn't "feel anything." Miranda reports that she rarely has sexual fantasies and generally does not feel a strong urge to engage in sexual behaviors. Miranda is planning to marry in two months and wants to increase her interest in sex before her wedding. She has not told her partner that she doesn't feel anything and does not want him to know she is seeking help. Miranda works as school teacher at a middle school, and she relates that her work is becoming increasingly stressful. She becomes distracted during the day because she worries that her fiance will think less of her if he finds out she is seeking help for this issue. The stress has become so bad that she has recently snapped at a student, and the students' parents have had to talk with her about the issue.
What diagnosis would be most appropriate for Miranda? Assess her degree of functional impairment, and include additional information about psychosocial stressors or concerns in Miranda's life right now. What could Miranda's therapist suggest as a viable treatment?

The table below gives the number of hours spent unsupervised each day as well as the overall grade averages for seven randomly selected middle school students. Using this data, consider the equation of the regression line, y^=b0+b1x, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant.

Step 1 of 6:

Find the estimated slope. Round your answer to three decimal places.

Step 2 of 6:

Find the estimated y-intercept. Round your answer to three decimal places.

Step 3 of 6:

Substitute the values you found in steps 1 and 2 into the equation for the regression line to find the estimated linear model. According to this model, if the value of the independent variable is increased by one unit, then find the change in the dependent variable y^.

Step 4 of 6:

Determine if the statement "All points predicted by the linear model fall on the same line" is true or false.

Step 5 of 6:

Determine the value of the dependent variable y^ at x=0.

(choose one)

b0, b1, x, y

Step 6 of 6:

Find the value of the coefficient of determination. Round your answer to three decimal places.

You are conducting a study to determine if there is a relationship between annual household income and a high school student’s GPA. The school district you are studying is diverse and lower income.

a) Before you conduct the study, do you expect there to be an association between these two variables? Why or why not? Which should be the explanatory variable?

b) You collect data from a random sample of 15 students. The first row of the table is household income of a particular student (in thousands of dollars) and the second row is the GPA of that particular student.

c) Does the data have a scatterplot that shows a linear association? What is the correlation coefficient? What does it tell you about the association between these two variables?

d) Use the above data to make a linear (regression) model.

e) Use the model to predict the GPA of a high-schooler that comes from a family that has a household income of $48,000.

f) How accurate is the model’s prediction of GPA for the family that makes $44,000?

g) If a family’s income increases by $10,000, what is the amount of change in a student’s GPA, as predicted by the model?

h) Statisticians often state “correlation is not necessarily causation.” Would it be correct to conclude that household income is “causing” GPA? Is it possible that there are other variables that are “lurking,” causing GPA and household income to be correlated? What might these variables be?

Assignment #8: Chi-Square Test of Independence

Directions: Use the Crosstabs option in the Descriptives menu to answer the questions based on the following scenario. (Be sure to select Chi-square from the Statistics submenu and Observed, Expected, Row, and Column in the Cells submenu. Assume a level of significance of .05)

The school district recently adopted the use of e-textbooks, and the superintendent is interested in determining the level of satisfaction with e-textbooks among students and if there is a relationship between the level of satisfaction and student classification. The superintendent selected a sample of students from one high school and asked them how satisfied they were with the use of e-textbooks. The data that were collected are presented in the following table.

          Student Classification

1. Of the students that were satisfied, what percent were Freshmen, Sophomore, Junior, and Senior? (Round your final answer to 1 decimal place).

2. State an appropriate null hypothesis for this analysis.

3. What is the value of the chi-square statistic? The value of chi-square is 7.12.

4. What are the reported degrees of freedom? The df is 3.

5. What is the reported level of significance? The reported level of significance is .052.

6. Based on the results of the chi-square test of independence, is there an association between e-textbook satisfaction and academic classification?

7. Present the results as they might appear in an article. This must include a table and narrative statement that reports and interprets the results of the analysis.

Note: The table must be created using your word processing program. Tables that are copied and pasted from SPSS are not acceptable.

Assignment #8: Chi-Square Test of Independence

Directions: Use the Crosstabs option in the Descriptives menu to answer the questions based on the following scenario. (Be sure to select Chi-square from the Statistics submenu and Observed, Expected, Row, and Column in the Cells submenu. Assume a level of significance of .05)

The school district recently adopted the use of e-textbooks, and the superintendent is interested in determining the level of satisfaction with e-textbooks among students and if there is a relationship between the level of satisfaction and student classification. The superintendent selected a sample of students from one high school and asked them how satisfied they were with the use of e-textbooks. The data that were collected are presented in the following table.

Student Classification
Sophomore Junior Senior

Satisfied Freshmen
Yes 18 19 13 12

No 13 14 15 17

1. Of the students that were satisfied, what percent were Freshmen, Sophomore, Junior, and Senior? (Round your final answer to 1 decimal place).

2. State an appropriate null hypothesis for this analysis.

3. What is the value of the chi-square statistic?

4. What are the reported degrees of freedom?

5. What is the reported level of significance?

6. Based on the results of the chi-square test of independence, is there an association between e-textbook satisfaction and academic classification?

7. Present the results as they might appear in an article. This must include a table and narrative statement that reports and interprets the results of the analysis.

   Note: The table must be created using your word processing program. Tables that are copied and pasted from SPSS are not acceptable.

The table below gives the number of hours spent unsupervised each day as well as the overall grade averages for seven randomly selected middle school students. Using this data, consider the equation of the regression line, yˆ=b0+b1xy^=b0+b1x, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant.

Step 1 of 6:

Find the estimated slope. Round your answer to three decimal places.

Step 2 of 6:

Find the estimated y-intercept. Round your answer to three decimal places.

Step 3 of 6:

Substitute the values you found in steps 1 and 2 into the equation for the regression line to find the estimated linear model. According to this model, if the value of the independent variable is increased by one unit, then find the change in the dependent variable yˆy^.

Step 4 of 6:

Determine the value of the dependent variable yˆy^ at x=0x=0.

Step 5 of 6:

Find the estimated value of y when x=3x=3. Round your answer to three decimal places.

Step 6 of 6:

Find the value of the coefficient of determination. Round your answer to three decimal places.