# 2753 Trend Lines & Forecasting (No Seasonality)

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| By Anthony Nunan
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Anthony Nunan
Community Contributor
Quizzes Created: 132 | Total Attempts: 44,116
Questions: 50 | Attempts: 201

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• 1.

### Using the data set above (TS7E8), write the equation for the trend line. (2 decimal places,no spaces) If the data is not suited to a trend line type 'none'

Explanation
The equation y=10.38+0.13x represents the trend line for the given data set TS7E8. The equation suggests that there is a linear relationship between the dependent variable y and the independent variable x. The slope of the line is 0.13, indicating that for each unit increase in x, y increases by 0.13 units. The y-intercept is 10.38, which represents the expected value of y when x is equal to zero. Therefore, this equation accurately represents the trend line for the given data set.

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• 2.

### From the time series plot above, should you apply a trend line to the raw data?

• A.

Yes, it appears to have random variation only.

• B.

No, it appears to have seasonal variation that need to be deseasonalised

• C.

No, it appears to have cyclic variation that needs to be randomised

• D.

Yes, it appears to have cyclic variation

B. No, it appears to have seasonal variation that need to be deseasonalised
• 3.

### From the time series plot above, should you apply a trend line to the raw data?

• A.

Yes, it appears to have random variation only.

• B.

No, it appears to have seasonal variation that needs to be deseasonalised

• C.

No, it appears to have cyclic variation that needs to be randomised

• D.

Yes, it appears to have cyclic variation

B. No, it appears to have seasonal variation that needs to be deseasonalised
Explanation
The correct answer is No, it appears to have seasonal variation that needs to be deseasonalised. This is because the time series plot shows a repeating pattern or seasonality, indicating that there are regular fluctuations in the data over a specific time period. To analyze the underlying trend in the data, it is necessary to remove the seasonal component through deseasonalization techniques.

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• 4.

### From the time series plot above, should you apply a trend line to the raw data?

• A.

Yes, it appears to have random variation only.

• B.

No, it appears to have seasonal variation that needs to be deseasonalised

• C.

No, it appears to have cyclic variation

• D.

Yes, it appears to have cyclic variation

B. No, it appears to have seasonal variation that needs to be deseasonalised
Explanation
Based on the given information, the time series plot shows that there is seasonal variation in the data. Therefore, it is recommended to apply a trend line to the raw data in order to deseasonalize it and remove the seasonal variation.

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• 5.

### From the time series plot above, should you apply a trend line to the raw data?

• A.

Yes, it appears to have random variation only.

• B.

No, it appears to have seasonal variation that needs to be deseasonalised

• C.

No, it appears to have cyclic variation

• D.

Yes, it appears to have cyclic variation