Trend – NBC Institute

QTB – May 2017 – L1 – SA – Q14 – Statistics

This question involves identifying the estimable components of a time series.

Question

The TWO components of a Time Series which are usually estimable are:
A. Trend and Cyclic variation
B. Seasonal variation and Trend
C. Random movements and Trend
D. Seasonal variation and Random movements
E. Cyclic variation and Seasonal variation

Answer

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Tags: Forecasting, Seasonal Variation, Time series, Trend
Level: Level 1

Topic: Statistics
Series: MAY 2017

QT – Nov 2016 – L1 – Q7 – Forecasting

Analyze absenteeism trends using time series and forecasting techniques for Dropper Ltd.

Question

The personnel department of Dropper Ltd, a large cocoa processing company in DropperLand, is concerned about absenteeism among its shop floor workforce. The mean number of absentees per day for each quarter of the years 1999 to 2001 and Quarter 1 in 2002 is given in the table below:

	Q1	Q2	Q3	Q4
1999	25.10	14.40	9.50	23.70
2000	27.90	16.90	12.40	26.10
2001	31.40	19.70	15.90	29.90
2002	34.50	–	–	–

Required:
a) Plot the data on a graph, leaving space for the remaining 2002 figures. (3 marks)

b) Using the method of 2-quarterly centered moving averages,
i) Determine the trend in the series and superimpose this on your graph in (a). (4 marks)
ii) Determine the equation of the trend line above by considering only the first and last centered moving average value on your graph in (i). (3 marks)

c) Using an appropriate decomposition model, determine the seasonal variations in the data. Give reasons for your choice of model. (5 marks)

d) Use your analysis above to roughly forecast the mean number of absentees for the remaining quarters of 2002. Comment on your forecast. (5 marks)

Answer

Find Related Questions by Tags, levels, etc.

Tags: Absenteeism, Forecasting, Seasonal Variations, Time series, Trend
Level: Level 1

Topic: Forecasting
Series: NOV 2016

QT – Nov 2015 – L1 – Q1a – Forecasting

State the four factors commonly found in time series data.

Question

State the four (4) factors which may be present in a Time Series Data. (4 Marks)

Answer

Find Related Questions by Tags, levels, etc.

Tags: Cyclical, Factors, Forecasting, Random, Seasonal, Time series, Trend
Level: Level 1

Topic: Forecasting
Series: NOV 2015

QTB – May 2017 – L1 – SA – Q14 – Statistics

This question involves identifying the estimable components of a time series.

Question

Answer

Find Related Questions by Tags, levels, etc.

Tags: Forecasting, Seasonal Variation, Time series, Trend
Level: Level 1

Topic: Statistics
Series: MAY 2017

QT – Nov 2016 – L1 – Q7 – Forecasting

Analyze absenteeism trends using time series and forecasting techniques for Dropper Ltd.

Question

	Q1	Q2	Q3	Q4
1999	25.10	14.40	9.50	23.70
2000	27.90	16.90	12.40	26.10
2001	31.40	19.70	15.90	29.90
2002	34.50	–	–	–

Required:
a) Plot the data on a graph, leaving space for the remaining 2002 figures. (3 marks)

c) Using an appropriate decomposition model, determine the seasonal variations in the data. Give reasons for your choice of model. (5 marks)

d) Use your analysis above to roughly forecast the mean number of absentees for the remaining quarters of 2002. Comment on your forecast. (5 marks)

Answer

Find Related Questions by Tags, levels, etc.

Tags: Absenteeism, Forecasting, Seasonal Variations, Time series, Trend
Level: Level 1

Topic: Forecasting
Series: NOV 2016

QT – Nov 2015 – L1 – Q1a – Forecasting

State the four factors commonly found in time series data.

Question

State the four (4) factors which may be present in a Time Series Data. (4 Marks)

Answer

Find Related Questions by Tags, levels, etc.

Tags: Cyclical, Factors, Forecasting, Random, Seasonal, Time series, Trend
Level: Level 1

Topic: Forecasting
Series: NOV 2015

Question Tag: Trend

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QTB – May 2017 – L1 – SA – Q14 – Statistics

This question involves identifying the estimable components of a time series.

QT – Nov 2016 – L1 – Q7 – Forecasting

Analyze absenteeism trends using time series and forecasting techniques for Dropper Ltd.

QT – Nov 2015 – L1 – Q1a – Forecasting

State the four factors commonly found in time series data.

QTB – May 2017 – L1 – SA – Q14 – Statistics

This question involves identifying the estimable components of a time series.

QT – Nov 2016 – L1 – Q7 – Forecasting

Analyze absenteeism trends using time series and forecasting techniques for Dropper Ltd.

QT – Nov 2015 – L1 – Q1a – Forecasting

State the four factors commonly found in time series data.

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QTB – May 2017 – L1 – SA – Q14 – Statistics

This question involves identifying the estimable components of a time series.

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QT – Nov 2016 – L1 – Q7 – Forecasting

Analyze absenteeism trends using time series and forecasting techniques for Dropper Ltd.

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QT – Nov 2015 – L1 – Q1a – Forecasting

State the four factors commonly found in time series data.

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QTB – May 2017 – L1 – SA – Q14 – Statistics

This question involves identifying the estimable components of a time series.

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QT – Nov 2016 – L1 – Q7 – Forecasting

Analyze absenteeism trends using time series and forecasting techniques for Dropper Ltd.

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QT – Nov 2015 – L1 – Q1a – Forecasting

State the four factors commonly found in time series data.

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