Question Tag: Linear Regression

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  • 20 Marks

PM – May 2021 – L2 – Q3 – Cost-Volume-Profit (CVP) Analysis

Forecast future sales using historical data and analyze which data period provides a better basis for forecasting.

Some time ago, Robert launched a new product. Initially, sales were strong, but recent figures have raised concerns. Robert seeks a more accurate sales forecast to create detailed cash projections. The sales data below illustrates an underlying trend derived from an averaging method:

Year Quarter Trend Point (x) Sales (Cartons) (y)
2016 3rd 1 10,000
2016 4th 2 10,760
2017 1st 3 10,920
2017 2nd 4 11,000
2017 3rd 5 11,050
2017 4th 6 11,080
2018 1st 7 11,085
2018 2nd 8 11,095
2018 3rd 9 11,120
2018 4th 10 11,130

On average, quarters 1 and 3 are 5% and 6% above the trend, respectively, while quarters 2 and 4 are 2% and 9% below it. Preliminary calculations for the 10 periods yield:

  • Linear Regression: y = a + bx
  • Slope: 82.67
  • Intercept: 10,472.33
  • Coefficient of determination: 0.535

Forecasting is needed for quarters 3 and 4 in 2019 and quarters 1 and 2 in 2020. There is a debate about using data from all 10 periods versus only the last 5. Analysis for the last five periods includes:

Results of last five periods‟ observations

(Note: y values are scaled down by 100 for ease of calculation.)

Required:
a. Forecast sales for the four quarters using the 10-period data. (8 Marks)
b. Prepare similar forecasts using the last five periods of data. (8 Marks)
c. Evaluate which data set provides the better forecast. (4 Marks)

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  • 20 Marks

MI – May 2017 – L1 – SB – Q2 – Forecasting Techniques

Determine fixed and variable costs using high-low method and linear regression analysis.

MICRA Manufacturing Company makes a product named as VATA. The records of some of the manufacturing expenses are easily identified as fixed or directly varied with production. The cost accountant of the company is confronted with the problem of preparing a budget for the coming year and wishes to determine the fixed and variable elements of the mixed factory overhead.

The following monthly information in respect of output and mixed factory overhead are provided as follows:

MONTH NUMBER OF UNITS (x) MIXED FACTORY OVERHEAD (y)
JANUARY 150 80
FEBRUARY 200 100
MARCH 300 135
APRIL 250 125
MAY 300 130
JUNE 250 120
JULY 350 140
AUGUST 300 125
SEPTEMBER 250 115
OCTOBER 150 80

Required:

a. Calculate the fixed and variable elements of the above mixed factory overhead using the high and low method. (5 Marks)

b. Use the linear regression analysis and determine the line of best fit. (15 Marks)

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  • 20 Marks

QT – May 2016 – L1 – Q2 – Forecasting

This question asks for the creation of a linear regression trend equation, seasonal components, and forecasts for chocolate sales.

Countess Company trades in bars of Golden Tree Chocolate from Tema Cocoa Processing Company Limited. The number of bars of chocolate sold per quarter over a four-year period by Countess Company is:

YEAR QUARTER 1 QUARTER 2 QUARTER 3 QUARTER 4
1 20 10 4 11
2 33 17 9 18
3 45 23 11 25
4 60 30 13 29

Required:

i) Plot the data on a graph (3 marks)

ii) Calculate a linear regression trend equation for the data (5 marks)

iii) Calculate the four seasonal components using a multiplicative model (5 marks)

iv) Forecast the number of bars of chocolate for the next two years (5 marks)

v) Comment on the reliability of the forecasts in iv) above (2 marks)

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  • 20 Marks

IMAC – DEC 2022 – L1 – Q5 – Cost Segregation and Estimation | Cost-Volume-Profit (CVP) Analysis

Estimation of fixed and variable costs using linear regression and discussion of assumptions underlying Cost-Volume-Profit (CVP) analysis.

a) Total production costs each week in a production department have been measured for the past five weeks, as follows:

Week Units Produced Total Cost (GH¢000)
1 5 20
2 9 27
3 4 17
4 5 19
5 6 23

Required:
i) Use linear regression analysis to obtain an estimate of fixed costs per week and the variable cost of production per unit (see formula table). (8 marks)
ii) Use your results to estimate total costs in a week when 8 units are produced. (3 marks)
iii) Explain why the regression analysis method of separating cost is considered more accurate than the high-low method. (4 marks)

b) The cost-volume-profit (CVP) analysis, also commonly known as breakeven analysis, looks to determine the breakeven point for different sales volumes and cost structures, which can be useful for managers making short-term business decisions. For CVP analysis to be effective, several assumptions are usually made.

Required:
State FOUR (4) assumptions underlying cost-volume-profit (CVP) analysis. (5 marks)

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  • 20 Marks

PM – May 2021 – L2 – Q3 – Cost-Volume-Profit (CVP) Analysis

Forecast future sales using historical data and analyze which data period provides a better basis for forecasting.

Some time ago, Robert launched a new product. Initially, sales were strong, but recent figures have raised concerns. Robert seeks a more accurate sales forecast to create detailed cash projections. The sales data below illustrates an underlying trend derived from an averaging method:

Year Quarter Trend Point (x) Sales (Cartons) (y)
2016 3rd 1 10,000
2016 4th 2 10,760
2017 1st 3 10,920
2017 2nd 4 11,000
2017 3rd 5 11,050
2017 4th 6 11,080
2018 1st 7 11,085
2018 2nd 8 11,095
2018 3rd 9 11,120
2018 4th 10 11,130

On average, quarters 1 and 3 are 5% and 6% above the trend, respectively, while quarters 2 and 4 are 2% and 9% below it. Preliminary calculations for the 10 periods yield:

  • Linear Regression: y = a + bx
  • Slope: 82.67
  • Intercept: 10,472.33
  • Coefficient of determination: 0.535

Forecasting is needed for quarters 3 and 4 in 2019 and quarters 1 and 2 in 2020. There is a debate about using data from all 10 periods versus only the last 5. Analysis for the last five periods includes:

Results of last five periods‟ observations

(Note: y values are scaled down by 100 for ease of calculation.)

Required:
a. Forecast sales for the four quarters using the 10-period data. (8 Marks)
b. Prepare similar forecasts using the last five periods of data. (8 Marks)
c. Evaluate which data set provides the better forecast. (4 Marks)

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  • 20 Marks

MI – May 2017 – L1 – SB – Q2 – Forecasting Techniques

Determine fixed and variable costs using high-low method and linear regression analysis.

MICRA Manufacturing Company makes a product named as VATA. The records of some of the manufacturing expenses are easily identified as fixed or directly varied with production. The cost accountant of the company is confronted with the problem of preparing a budget for the coming year and wishes to determine the fixed and variable elements of the mixed factory overhead.

The following monthly information in respect of output and mixed factory overhead are provided as follows:

MONTH NUMBER OF UNITS (x) MIXED FACTORY OVERHEAD (y)
JANUARY 150 80
FEBRUARY 200 100
MARCH 300 135
APRIL 250 125
MAY 300 130
JUNE 250 120
JULY 350 140
AUGUST 300 125
SEPTEMBER 250 115
OCTOBER 150 80

Required:

a. Calculate the fixed and variable elements of the above mixed factory overhead using the high and low method. (5 Marks)

b. Use the linear regression analysis and determine the line of best fit. (15 Marks)

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  • 20 Marks

QT – May 2016 – L1 – Q2 – Forecasting

This question asks for the creation of a linear regression trend equation, seasonal components, and forecasts for chocolate sales.

Countess Company trades in bars of Golden Tree Chocolate from Tema Cocoa Processing Company Limited. The number of bars of chocolate sold per quarter over a four-year period by Countess Company is:

YEAR QUARTER 1 QUARTER 2 QUARTER 3 QUARTER 4
1 20 10 4 11
2 33 17 9 18
3 45 23 11 25
4 60 30 13 29

Required:

i) Plot the data on a graph (3 marks)

ii) Calculate a linear regression trend equation for the data (5 marks)

iii) Calculate the four seasonal components using a multiplicative model (5 marks)

iv) Forecast the number of bars of chocolate for the next two years (5 marks)

v) Comment on the reliability of the forecasts in iv) above (2 marks)

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  • 20 Marks

IMAC – DEC 2022 – L1 – Q5 – Cost Segregation and Estimation | Cost-Volume-Profit (CVP) Analysis

Estimation of fixed and variable costs using linear regression and discussion of assumptions underlying Cost-Volume-Profit (CVP) analysis.

a) Total production costs each week in a production department have been measured for the past five weeks, as follows:

Week Units Produced Total Cost (GH¢000)
1 5 20
2 9 27
3 4 17
4 5 19
5 6 23

Required:
i) Use linear regression analysis to obtain an estimate of fixed costs per week and the variable cost of production per unit (see formula table). (8 marks)
ii) Use your results to estimate total costs in a week when 8 units are produced. (3 marks)
iii) Explain why the regression analysis method of separating cost is considered more accurate than the high-low method. (4 marks)

b) The cost-volume-profit (CVP) analysis, also commonly known as breakeven analysis, looks to determine the breakeven point for different sales volumes and cost structures, which can be useful for managers making short-term business decisions. For CVP analysis to be effective, several assumptions are usually made.

Required:
State FOUR (4) assumptions underlying cost-volume-profit (CVP) analysis. (5 marks)

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You're reporting an error for "IMAC – DEC 2022 – L1 – Q5 – Cost Segregation and Estimation | Cost-Volume-Profit (CVP) Analysis"

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