Additive model – NBC Institute

MI – May 2024 – L1 – SB – Q1 – Forecasting Techniques-Analysis, Moving Averages

Analyze a time series and describe two models for estimating seasonal variation.

Question

a. Describe how a time series can be analyzed. (10 Marks)

b. “There are TWO models used to estimate seasonal variation.” List and briefly describe the TWO models. (10 Marks)

Answer

Find Related Questions by Tags, levels, etc.

Tags: Additive model, Moving Averages, Proportional Model, Seasonal Variation, Time series
Level: Level 1

Topic: Forecasting Techniques-Analysis, Moving Averages
Series: MAY 2024

QT – Nov 2018 – L1 – Q6a – Forecasting

State the two main models of time series analysis.

Question

State the TWO (2) main models of time series analysis. (2 marks)

Answer

Find Related Questions by Tags, levels, etc.

Tags: Additive model, Forecasting, Models, Multiplicative Model, Time series
Level: Level 1

Topic: Forecasting
Series: NOV 2018

QT – Nov 2015 – L1 – Q1b – Forecasting

Calculate the trend, average seasonal variation, and forecast for Year 4 using a 4-point centered moving average method for Golden Tree Chocolate Bar sales.

Question

Quarterly sales of a Golden Tree Chocolate Bar at a popular mall in KoKoLand City are given as follows:

YEAR	QUARTER 1	QUARTER 2	QUARTER 3	QUARTER 4
1	1260	756	588	1596
2	1352	966	579	2028
3	1786	920	865	2273

Required:
(i) Calculate the trend in the series using a 4-point centered moving average method. (4 Marks)

(ii) Using (i), calculate the Average Seasonal Variation based on the Additive Model of Time Series analysis. (4 Marks)

(iii) Using the values in (ii), determine the Adjusted Average Seasonal Variation for the Time Series Data. (4 Marks)

(iv) Prepare Seasonal Adjusted Forecast for Year 4 using the Additive Model. (4 Marks)

Answer

Find Related Questions by Tags, levels, etc.

Tags: Additive model, Forecasting, Seasonal Variation, Time series, Trend Analysis
Level: Level 1

Topic: Forecasting
Series: NOV 2015

MI – May 2024 – L1 – SB – Q1 – Forecasting Techniques-Analysis, Moving Averages

Analyze a time series and describe two models for estimating seasonal variation.

Question

a. Describe how a time series can be analyzed. (10 Marks)

b. “There are TWO models used to estimate seasonal variation.” List and briefly describe the TWO models. (10 Marks)

Answer

Find Related Questions by Tags, levels, etc.

Tags: Additive model, Moving Averages, Proportional Model, Seasonal Variation, Time series
Level: Level 1

Topic: Forecasting Techniques-Analysis, Moving Averages
Series: MAY 2024

QT – Nov 2018 – L1 – Q6a – Forecasting

State the two main models of time series analysis.

Question

State the TWO (2) main models of time series analysis. (2 marks)

Answer

Find Related Questions by Tags, levels, etc.

Tags: Additive model, Forecasting, Models, Multiplicative Model, Time series
Level: Level 1

Topic: Forecasting
Series: NOV 2018

QT – Nov 2015 – L1 – Q1b – Forecasting

Calculate the trend, average seasonal variation, and forecast for Year 4 using a 4-point centered moving average method for Golden Tree Chocolate Bar sales.

Question

Quarterly sales of a Golden Tree Chocolate Bar at a popular mall in KoKoLand City are given as follows:

YEAR	QUARTER 1	QUARTER 2	QUARTER 3	QUARTER 4
1	1260	756	588	1596
2	1352	966	579	2028
3	1786	920	865	2273

Required:
(i) Calculate the trend in the series using a 4-point centered moving average method. (4 Marks)

(ii) Using (i), calculate the Average Seasonal Variation based on the Additive Model of Time Series analysis. (4 Marks)

(iii) Using the values in (ii), determine the Adjusted Average Seasonal Variation for the Time Series Data. (4 Marks)

(iv) Prepare Seasonal Adjusted Forecast for Year 4 using the Additive Model. (4 Marks)

Answer

Find Related Questions by Tags, levels, etc.

Tags: Additive model, Forecasting, Seasonal Variation, Time series, Trend Analysis
Level: Level 1

Topic: Forecasting
Series: NOV 2015

Question Tag: Additive model

Filter by Professional Bodies

Filter by Subject

Filter by Series

Filter by Topics

Filter by Levels

MI – May 2024 – L1 – SB – Q1 – Forecasting Techniques-Analysis, Moving Averages

Analyze a time series and describe two models for estimating seasonal variation.

QT – Nov 2018 – L1 – Q6a – Forecasting

State the two main models of time series analysis.

QT – Nov 2015 – L1 – Q1b – Forecasting

Calculate the trend, average seasonal variation, and forecast for Year 4 using a 4-point centered moving average method for Golden Tree Chocolate Bar sales.

MI – May 2024 – L1 – SB – Q1 – Forecasting Techniques-Analysis, Moving Averages

Analyze a time series and describe two models for estimating seasonal variation.

QT – Nov 2018 – L1 – Q6a – Forecasting

State the two main models of time series analysis.

QT – Nov 2015 – L1 – Q1b – Forecasting

Calculate the trend, average seasonal variation, and forecast for Year 4 using a 4-point centered moving average method for Golden Tree Chocolate Bar sales.

Our offerings

Contact Info

Customer

Get In Touch

Question Tag: Additive model

Filter by Professional Bodies

Filter by Subject

Filter by Series

Filter by Topics

Filter by Levels

MI – May 2024 – L1 – SB – Q1 – Forecasting Techniques-Analysis, Moving Averages

Analyze a time series and describe two models for estimating seasonal variation.

You're reporting an error for "MI – May 2024 – L1 – SB – Q1 – Forecasting Techniques-Analysis, Moving Averages"

QT – Nov 2018 – L1 – Q6a – Forecasting

State the two main models of time series analysis.

You're reporting an error for "QT – Nov 2018 – L1 – Q6a – Forecasting"

QT – Nov 2015 – L1 – Q1b – Forecasting

Calculate the trend, average seasonal variation, and forecast for Year 4 using a 4-point centered moving average method for Golden Tree Chocolate Bar sales.

You're reporting an error for "QT – Nov 2015 – L1 – Q1b – Forecasting"

MI – May 2024 – L1 – SB – Q1 – Forecasting Techniques-Analysis, Moving Averages

Analyze a time series and describe two models for estimating seasonal variation.

You're reporting an error for "MI – May 2024 – L1 – SB – Q1 – Forecasting Techniques-Analysis, Moving Averages"

QT – Nov 2018 – L1 – Q6a – Forecasting

State the two main models of time series analysis.

You're reporting an error for "QT – Nov 2018 – L1 – Q6a – Forecasting"

QT – Nov 2015 – L1 – Q1b – Forecasting

Calculate the trend, average seasonal variation, and forecast for Year 4 using a 4-point centered moving average method for Golden Tree Chocolate Bar sales.

You're reporting an error for "QT – Nov 2015 – L1 – Q1b – Forecasting"

Our offerings

Contact Info

Customer

Get In Touch

admin