Q.3.1Calculate the carrying amount of the cargo planes at 31 December 2022.Round all figures to the nearest rand.Q.3.2Prepare the journal entries in respect of the warehouse for the year ended31 December 2022.Journal Narrations are required.Q.3.3Do you agree with the sentiments of the Financial Director? Substantiate youranswer with reference to the requirements of IAS 16.Q.3.4Prepare the Property, plant and equipment note to the financial statements ofFHL Limited for the year ended 31 December 2022.Accounting policy notes are not required.Comparative numbers are not required. The following table indicates the ages of a sample of female employees of People Plus Pty, andthe corresponding monthly income of each employee (in thousands of Rands).Age In Years (x)Monthly Income (RO00s) (y)4043494932362731384146423y completing the table given below, and then applying the relevant formulae,determine the linear regression function for this bivariate data set.yхуТОTALIf a female employee is 39 years of age, estimate her monthly income.

As per our protocol we provide solution to the one question only but as you have asked two questions…

3y completing the table given below, and then applying the relevant formulae, determine the linear regression function for this bivariate data set. y x? ху ТОTAL If a female employee is 39 years of age, estimate her monthly income.

3y completing the table given below, and then applying the relevant formulae, determine the linear regression function for this bivariate data set. y x? ху ТОTAL If a female employee is 39 years of age, estimate her monthly income.

Essentials of Business Analytics (MindTap Course List)

2nd Edition

ISBN:9781305627734

Author:Jeffrey D. Camm, James J. Cochran, Michael J. Fry, Jeffrey W. Ohlmann, David R. Anderson

Publisher:Jeffrey D. Camm, James J. Cochran, Michael J. Fry, Jeffrey W. Ohlmann, David R. Anderson

Chapter8: Time Series Analysis And_forecasting

Section: Chapter Questions

Problem 14P: The following time series shows the sales of a particular product over the past 12...

See similar textbooks

Similar questions

A marketing professor at Givens College is interested in the relationship between hours spent studying and total points earned in a course. Data collected on 156 students who took the course last semester are provided in the tile MktHrsPts. Develop a scatter chart for these data. What does the scatter chart indicate about the relationship between total points earned and hours spent studying? Develop an estimated regression equation showing how total points earned is related to hours spent studying. What is the estimated regression model? Test whether each of the regression parameters β0 and β1 is equal to zero at a 0.01 level of significance. What are the correct interpretations of the estimated regression parameters? Are these interpretations reasonable? How much of the variation in the sample values of total point earned does the model you estimated in part (b) explain? Mark Sweeney spent 95 hours studying. Use the regression model you estimated in part (b) to predict the total points Mark earned.
Consider the following time series data: Construct a time series plot. What type of pattern exists in the data? Use a multiple regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data: Qtr1 = 1 if quarter 1, 0 otherwise; Qtr2 = 1 if quarter 2. 0 otherwise; Qtr3 = 1 if quarter 3, 0 otherwise. Compute the quarterly forecasts for next year based on the model you developed in part (b). Use a multiple regression model to develop an equation to account for trend and seasonal effects in the data. Use the dummy variables you developed in part (b) to capture seasonal effects and create a variable t such that t = 1 for quarter 1 in year 1, t = 2 for quarter 2 in year 1, … t = 12 for quarter 4 in year 3. Compute the quarterly forecasts for next year based on the model you developed in part (d). Is the model you developed in part (b) or the model you developed in part (d) more effective? Justify your answer.
In this chapter we showed how a simple random sample of 30 EAI employees can be used to develop point estimates of the population mean annual salary, the population standard deviation for annual salary, and the population proportion having completed the management training program. a. Use Excel to select a simple random sample of 50 EAI employees. b. Develop a point estimate of the mean annual salary. c. Develop a point estimate of the population standard deviation for annual salary. d. Develop a point estimate of the population proportion having completed the management training program.
Income tax returns show that the mean income of self-employed persons in aparticular year was £15,000, with a standard deviation of £975. A randomsample of 169 returns from people in the clothing industry gave a mean income of £14,500. Did this indicate that income from self-employment in the clothing industry was significantly different?
Let p be the population proportion for the following condition. Find the point estimates for p and q. A study of 4263 adults from country A, 2843 think mainstream media is more interested in making money than in telling the truth. The point estimate for p, p, is (Round to three decimal places a
The known standard deviation in salary for all mid-level professionals in the financial industry is $11,000. Company A and Company B are in the financial industry. Suppose samples are taken of mid-level professionals from Company A and from Company B. The sample mean salary for mid-level professionals in Company A is $80,000. The sample mean salary for mid-level professionals in Company B is $96,000. Company A and Company B management want to know if their mid-level professionals are paid differently, on average.
The following data, taken from 8 towns in Alberta, are the percentage of residents who are university graduates and the median household incomes (in $ 1000's) for all households in each town. Graduates (%) Median Income ($ 1000) 61.7 47.6 50.9 34.1 57.1 31.5 56.4 41.3 42.8 34.5 42.1 28.1 33.2 23.1 19.2 20.4 (a) State the slope term and the Y -intercept term of the least squares regression line which attempts to predict the median income of a town in Alberta based on its linear relationship with the percentage of residents who are university graduates.(b) Find the correlation coefficient(c) As the percenage of university graduates increases by 10%, the median income will change (in $ 1000s) by (make sure you include the positive or negative sign) (d) What percentage of the variation in the variable Median Income is not explained by its linear relationship to the variable Percentage of University Graduates? Use at least one place after the decimal.(e) Using your…
On January 1 2020, South by Southwest Company used least squares regression analysis to estimate the total monthly payroll department cost of the company in 2020. The followings are the output from the regression analysis based on the observation of the payroll department cost( dependent variable) and the labor hours worked ( independent variable) for the last 20 months: Constant $18,000 r2 0.8924 X coefficient(s) $ 2.55 Required: BASED ON THE OUTPUT FROM THE REGRESSION ANALYSIS a. What is the total estimated fixed payroll department cost? b. What is the variable payroll department cost per labor hour? c. What is the estimate cost function of the payroll department cost? d. What is the coefficient of determination? Comment on the goodness of fit of the cost function? Plzz give all the ans
The following time series shows the sales of a particular product over the past 12 months. Construct a time series plot. What type of pattern exists in the data? Use α = 0.3 to compute the exponential smoothing values for the time series. Use trial and error to find a value of the exponential smoothing coefficient α that results in a relatively small MSE.
A sociologist was hired by a large city hospital to investigate the relationship between the number of unauthorized days that employees are absent per year and the distance (miles) between home and work for the employees. A sample of 10 employees was chosen, and the following data were collected. a. Develop a scatter chart for these data. Does a linear relationship appear reasonable? Explain. b. Use the data to develop an estimated regression equation that could be used to predict the number of days absent given the distance to work. What is the estimated regression model? c. What is the 99% confidence interval for the regression parameter 1? Based on this interval, what conclusion can you make about the hypotheses that the regression parameter 1 is equal to zero? d. What is the 99% confidence interval for the regression parameter 0? Based on this interval, what conclusion can you make about the hypotheses that the regression parameter 0 is equal to zero? e. How much of the variation in the sample values of number of days absent does the model you estimated in part (b) explain?
Consider the following time series: a. Construct a time series plot. What type of pattern exists in the data? Is there an indication of a seasonal pattern? b. Use a multiple linear regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data: Qtr1 = 1 if quarter 1, 0 otherwise; Qtr2 = 1 if quarter 2, 0 otherwise; Qtr3 = 1 if quarter 3, 0 otherwise. c. Compute the quarterly forecasts for next year.
The Economic Policy Institute periodically issues reports on wages of entry-level workers. The institute reported that entry-level wages for male college graduates were $21.68 per hour and for female college graduates were $18.80 per hour in 2011. Assume that the standard deviation for male graduates is $2.30, and for female graduates it is $2.05. What is the sampling distribution of for a random sample of 50 male college graduates? What is the sampling distribution of for a random sample of 50 female college graduates? In which of the preceding two cases, part (a) or part (b), is the standard error of smaller? Why?