Regression Analysis – NBC Institute

QT – Nov 2018 – L1 – Q1b – Forecasting

Determine the number of errors a student would make after 280 minutes of study and the expected change in errors for a 1-minute change.

Question

The study time in minutes and the number of errors on a mock examination paper made by ten (10) ICAG students are given below:

Student	1	2	3	4	5	6	7	8	9	10
Study Time (X)	90	100	130	150	180	200	220	300	350	400
Errors (Y)	25	28	20	20	15	12	13	10	8	6

(i) Determine how many errors a student would make in the examination if he studied for 280 minutes.

(ii) Determine the expected change in the number of errors if there is a 1-minute change in study time.

Answer

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Tags: Errors Prediction, Regression Analysis, Study Time
Level: Level 1

Topic: Forecasting
Series: NOV 2018

QT – Nov 2015 – L1 – Q3 – Forecasting

Calculate the regression line for maize demand and forecast demand for the first three months of the next year using regression analysis.

Question

The monthly demand for maize (in hundreds of bags) for the last year in Bosua Market is shown below:

Month	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec
Demand	42	43	40	44	50	47	53	49	54	57	63	60

Required:
(a) Calculate the regression line $y = a + b x$ for the data. (9 Marks)

(b) Using the regression line in (a), determine the forecast for next year:
(i) January, (1 Mark)
(ii) February, (1 Mark)
(iii) March. (1 Mark)

Answer

Find Related Questions by Tags, levels, etc.

Tags: Demand forecast, Forecasting, Regression Analysis, Standard error, Trend Analysis
Level: Level 1

Topic: Forecasting
Series: NOV 2015

IMAC – Nov 2021 – L1 – Q5 – Budgeting | Forecasting

Analysis of a regression equation related to absenteeism, seasonal variation in production output, and variance analysis for overheads.

Question

a) A large manufacturing company is investigating the cost of sickness amongst production workers who the company has employed for more than one year. The following regression equation, based on a random sample of 50 for such production workers, was derived for 2018:

$y = 15.6 - 1.2 x$

where $y$ represents the number of days absent in a year because of sickness and $x$ represents the number of years’ employment with the company.

Required: i) Explain the meaning of each component of the regression equation. (2 marks)
ii) Predict the number of days of absence through sickness to be expected of an employee who has been with the company for eight years. (2 marks)
iii) Explain TWO (2) limitations or problems of using this equation in practice. (4 marks)

b) A statistician is carrying out an analysis of a company’s production output. The output varies according to the year’s season, and, from the data, she has calculated the following seasonal variations in units of production:

QUARTER	1	2	3	4
Year 1			+11.2	+23.5
Year 2	-9.8	-28.1	+12.5	+23.7
Year 3	-7.4	-26.3	+11.7

Required: i) Calculate and explain the average quarterly variation for each quarter. (5 marks)
ii) If the trend output in the 4th Quarter of Year 3 is expected to be 10,536 units, what is the forecast output? (2 marks)

c) KK Ltd operates a standard absorption costing system and has provided the following costs data in relation to its prime product, Qwikpass:

Standard Cost Card:

	GH¢
Direct Material 4kg @ GH¢3/kg	12
Direct Labour 3hrs @ GH¢5/hr	15
Variable Overheads 3hrs @ GH¢3/hr	9
Fixed Overheads 3hrs @ GH¢2	6
Total Cost per Unit	42

Budgeted Units: 6,000

Actual Results:

	GH¢
Units produced	6,400
Direct Materials Purchased and used 32,000kg	144,000
Direct Labour 30,720hrs	199,680
Variable Overheads	138,240
Fixed Overheads	45,000
Total costs	526,920

Required: i) Compute the Variable Overheads Expenditure Variance. (1 mark)
ii) Compute the Fixed Overheads Expenditure Variance. (2 marks)
iii) Compute the Fixed Overheads Volume Variance. (2 marks)

Answer

Find Related Questions by Tags, levels, etc.

Tags: Absenteeism, Employment Years, Regression Analysis, Seasonal Variations, Sickness, Standard Costing, Variance Analysis
Level: Level 1

Topic: Budgeting, Forecasting
Series: NOV 2021

QT – Nov 2018 – L1 – Q1b – Forecasting

Determine the number of errors a student would make after 280 minutes of study and the expected change in errors for a 1-minute change.

Question

The study time in minutes and the number of errors on a mock examination paper made by ten (10) ICAG students are given below:

Student	1	2	3	4	5	6	7	8	9	10
Study Time (X)	90	100	130	150	180	200	220	300	350	400
Errors (Y)	25	28	20	20	15	12	13	10	8	6

(i) Determine how many errors a student would make in the examination if he studied for 280 minutes.

(ii) Determine the expected change in the number of errors if there is a 1-minute change in study time.

Answer

Find Related Questions by Tags, levels, etc.

Tags: Errors Prediction, Regression Analysis, Study Time
Level: Level 1

Topic: Forecasting
Series: NOV 2018

QT – Nov 2015 – L1 – Q3 – Forecasting

Calculate the regression line for maize demand and forecast demand for the first three months of the next year using regression analysis.

Question

The monthly demand for maize (in hundreds of bags) for the last year in Bosua Market is shown below:

Month	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec
Demand	42	43	40	44	50	47	53	49	54	57	63	60

Required:
(a) Calculate the regression line $y = a + b x$ for the data. (9 Marks)

(b) Using the regression line in (a), determine the forecast for next year:
(i) January, (1 Mark)
(ii) February, (1 Mark)
(iii) March. (1 Mark)

Answer

Find Related Questions by Tags, levels, etc.

Tags: Demand forecast, Forecasting, Regression Analysis, Standard error, Trend Analysis
Level: Level 1

Topic: Forecasting
Series: NOV 2015

IMAC – Nov 2021 – L1 – Q5 – Budgeting | Forecasting

Analysis of a regression equation related to absenteeism, seasonal variation in production output, and variance analysis for overheads.

Question

$y = 15.6 - 1.2 x$

where $y$ represents the number of days absent in a year because of sickness and $x$ represents the number of years’ employment with the company.

QUARTER	1	2	3	4
Year 1			+11.2	+23.5
Year 2	-9.8	-28.1	+12.5	+23.7
Year 3	-7.4	-26.3	+11.7

c) KK Ltd operates a standard absorption costing system and has provided the following costs data in relation to its prime product, Qwikpass:

Standard Cost Card:

	GH¢
Direct Material 4kg @ GH¢3/kg	12
Direct Labour 3hrs @ GH¢5/hr	15
Variable Overheads 3hrs @ GH¢3/hr	9
Fixed Overheads 3hrs @ GH¢2	6
Total Cost per Unit	42

Budgeted Units: 6,000

Actual Results:

	GH¢
Units produced	6,400
Direct Materials Purchased and used 32,000kg	144,000
Direct Labour 30,720hrs	199,680
Variable Overheads	138,240
Fixed Overheads	45,000
Total costs	526,920

Required: i) Compute the Variable Overheads Expenditure Variance. (1 mark)
ii) Compute the Fixed Overheads Expenditure Variance. (2 marks)
iii) Compute the Fixed Overheads Volume Variance. (2 marks)

Answer

Find Related Questions by Tags, levels, etc.

Tags: Absenteeism, Employment Years, Regression Analysis, Seasonal Variations, Sickness, Standard Costing, Variance Analysis
Level: Level 1

Topic: Budgeting, Forecasting
Series: NOV 2021

Question Tag: Regression Analysis

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QT – Nov 2018 – L1 – Q1b – Forecasting

Determine the number of errors a student would make after 280 minutes of study and the expected change in errors for a 1-minute change.

QT – Nov 2015 – L1 – Q3 – Forecasting

Calculate the regression line for maize demand and forecast demand for the first three months of the next year using regression analysis.

IMAC – Nov 2021 – L1 – Q5 – Budgeting | Forecasting

Analysis of a regression equation related to absenteeism, seasonal variation in production output, and variance analysis for overheads.

QT – Nov 2018 – L1 – Q1b – Forecasting

Determine the number of errors a student would make after 280 minutes of study and the expected change in errors for a 1-minute change.

QT – Nov 2015 – L1 – Q3 – Forecasting

Calculate the regression line for maize demand and forecast demand for the first three months of the next year using regression analysis.

IMAC – Nov 2021 – L1 – Q5 – Budgeting | Forecasting

Analysis of a regression equation related to absenteeism, seasonal variation in production output, and variance analysis for overheads.

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QT – Nov 2018 – L1 – Q1b – Forecasting

Determine the number of errors a student would make after 280 minutes of study and the expected change in errors for a 1-minute change.

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QT – Nov 2015 – L1 – Q3 – Forecasting

Calculate the regression line for maize demand and forecast demand for the first three months of the next year using regression analysis.

You're reporting an error for "QT – Nov 2015 – L1 – Q3 – Forecasting"

IMAC – Nov 2021 – L1 – Q5 – Budgeting | Forecasting

Analysis of a regression equation related to absenteeism, seasonal variation in production output, and variance analysis for overheads.

You're reporting an error for "IMAC – Nov 2021 – L1 – Q5 – Budgeting | Forecasting"

QT – Nov 2018 – L1 – Q1b – Forecasting

Determine the number of errors a student would make after 280 minutes of study and the expected change in errors for a 1-minute change.

You're reporting an error for "QT – Nov 2018 – L1 – Q1b – Forecasting"

QT – Nov 2015 – L1 – Q3 – Forecasting

Calculate the regression line for maize demand and forecast demand for the first three months of the next year using regression analysis.

You're reporting an error for "QT – Nov 2015 – L1 – Q3 – Forecasting"

IMAC – Nov 2021 – L1 – Q5 – Budgeting | Forecasting

Analysis of a regression equation related to absenteeism, seasonal variation in production output, and variance analysis for overheads.

You're reporting an error for "IMAC – Nov 2021 – L1 – Q5 – Budgeting | Forecasting"

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