Question 1

The Pyramids of Giza
 The Pyramids of Giza is one of the most visited monuments in Egypt.The number of visitors per quarter has been recorded (in thousands)as shown in the accompanying table:  ​ ​
-{The Pyramids of Giza Narrative} Calculate the four-quarter centered moving averages and use it to calculate the seasonal (quarterly)indexes.

Accepted Answer

The answer of The Pyramids of Giza
 The Pyramids of...

Question 2

The mean absolute deviation is the summation of the residuals divided by the sample size.

Accepted Answer

The mean absolute deviation is the average absolute difference between each data point and the mean of the dataset. It is calculated by summing the absolute values of the residuals (the differences between each data point and the mean) and dividing by the sample size.

Question 3

The Pyramids of Giza
 The Pyramids of Giza is one of the most visited monuments in Egypt.The number of visitors per quarter has been recorded (in thousands)as shown in the accompanying table:  ​ ​
-{The Pyramids of Giza Narrative} Use regression analysis to develop the trend line.

Accepted Answer

The answer of The Pyramids of Giza
 The Pyramids of...

Question 4

The Pyramids of Giza
 The Pyramids of Giza is one of the most visited monuments in Egypt.The number of visitors per quarter has been recorded (in thousands)as shown in the accompanying table:  ​ ​
-{The Pyramids of Giza Narrative} Use the seasonal indexes computed in the previous question to deseasonalize the original time series data,and plot the deseasonalized time series.

Accepted Answer

The answer of The Pyramids of Giza
 The Pyramids of...

Question 5

If we have 5 years of monthly observations,we may use the first four years to develop several competing forecasting models,and then use them to forecast the fifth year.Since we know the actual values in the fifth year,we can choose the technique that results in the most accurate forecast using either the mean absolute deviation (MAD)or the sum of squares for forecast error (SSE).

Accepted Answer

This statement is true. Using a portion of the data to develop competing forecasting models and then using the remaining data to test the accuracy of the models is a common practice in forecasting. MAD and SSE are both commonly used measures of forecast accuracy.

Question 6

Hotel Occupancy
A small hotel has recorded the number of rooms occupied during weekdays over a period of four weeks as is shown in the table below:

-{Hotel Occupancy Narrative} What do the daily indexes tell us?

Accepted Answer

The answer of Hotel Occupancy
A small hotel has recorded the...

Question 7

The mean absolute deviation averages the absolute differences between the actual values of the time series at time t and the forecast values at time t + 1.

Accepted Answer

The mean absolute deviation (MAD) averages the absolute differences between the actual values of the time series and the forecast values. The forecast values can be for any future time point, not just time t + 1.

Question 8

The Pyramids of Giza
 The Pyramids of Giza is one of the most visited monuments in Egypt.The number of visitors per quarter has been recorded (in thousands)as shown in the accompanying table:  ​ ​
-{The Pyramids of Giza Narrative} Use the seasonal indexes and the linear trend calculated in the previous questions to forecast the number of visitors in the next four quarters and describe the seasonal fluctuations in the number of visitors.

Accepted Answer

The answer of The Pyramids of Giza
 The Pyramids of...

Question 9

Hotel Occupancy
A small hotel has recorded the number of rooms occupied during weekdays over a period of four weeks as is shown in the table below:

-{Hotel Occupancy Narrative} Calculate the seasonal (daily)indexes.

Accepted Answer

The answer of Hotel Occupancy
A small hotel has recorded the...

Question 10

A time series is shown in the table below.  
a.Plot the time series.Would the linear or quadratic model fit better?
b.Use the regression technique to calculate the linear trend line and the quadratic trend line.Which model fits better?

Accepted Answer

The answer of A time series is shown in the...

Question 11

The most commonly used measures of forecast accuracy are the mean absolute deviation (MAD)and the sum of squares for forecast error (SSE).

Accepted Answer

MAD and SSE are indeed two commonly used measures of forecast accuracy.

Question 12

Hotel Occupancy
A small hotel has recorded the number of rooms occupied during weekdays over a period of four weeks as is shown in the table below:

-{Hotel Occupancy Narrative} Find the regression trend line.

Accepted Answer

The answer of Hotel Occupancy
A small hotel has recorded the...

Question 13

If the time series displays a gradual or no trend and no evidence of seasonal variation,exponential smoothing is not an effective as a forecasting method.

Accepted Answer

Exponential smoothing can be very effective for forecasting time series that display no trend or seasonal variation, as it focuses on smoothing out the noise and fluctuations in the data to predict future values.

Question 14

The mean absolute deviation is a measure of the average of the absolute discrepancies between the actual and the fitted values in a given time series.

Accepted Answer

The mean absolute deviation (MAD) is indeed a measure of the average of the absolute discrepancies between the actual and the fitted values in a given time series. MAD is typically used as a measure of forecast accuracy, and its value is calculated by taking the average of the absolute differences between the actual values and the forecast values over a period of time.

Question 15

If there is no obvious trend or seasonality in the time series data,and we believe that there is a correlation between consecutive residuals,the autoregressive model may be most effective as a forecasting technique.

Accepted Answer

The autoregressive model is designed to capture the correlation between consecutive residuals, and it can be effective in cases where there is no obvious trend or seasonality in the time series data. Therefore, the statement is true.

Question 16

If the time series is composed of seasonal variation and long-term trend,we can use seasonal indexes and the regression equation to forecast.

Accepted Answer

Seasonal indexes can be used to identify and quantify the seasonal variation in the data, while a regression equation can be used to model the long-term trend. By combining the two, we can create a forecast that takes into account both the seasonal and trend components of the time series.

Question 17

A time series is shown in the table below:  
a.Plot the time series to determine which of the trend models appears to fit better.
b.Use the regression technique to calculate the linear trend line and the quadratic trend line.Which line fits better? Use the best model to forecast the value of y for time period 7.

Accepted Answer

The answer of A time series is shown in the...

Question 18

The mean absolute deviation averages the absolute differences between the actual values of the time series at time t and the forecast values at time:

Accepted Answer

The mean absolute deviation (MAD) measures the average difference between the actual values and the forecast values. It is calculated as the average of the absolute differences between the actual and forecast values at each time point. Therefore, the time t is the reference point for the forecast, and the actual values are compared to the forecast values at that time point (t). Hence, the best choice is B, which corresponds to time t.

Question 19

Hotel Occupancy
A small hotel has recorded the number of rooms occupied during weekdays over a period of four weeks as is shown in the table below:

-{Hotel Occupancy Narrative} Calculate the seasonal indexes,based on the regression trend line developed in the previous question.

Accepted Answer

The answer of Hotel Occupancy
A small hotel has recorded the...

Question 20

Which method would you recommend to your statistics professor in selecting the appropriate forecasting model if avoiding large errors is extremely important to him or her?

Accepted Answer

The answer of Which method would you recommend to your...

Quiz 20: Time-Series Analytics and Forecasting

The mean absolute deviation is the summation of the residuals divided by the sample size.

The Pyramids of Giza The Pyramids of Giza is one of the most visited monuments in Egypt.The number of visitors per quarter has been recorded (in thousands)as shown in the accompanying table: -{The Pyramids of Giza Narrative} Use regression analysis to develop the trend line.

Hotel Occupancy A small hotel has recorded the number of rooms occupied during weekdays over a period of four weeks as is shown in the table below: -{Hotel Occupancy Narrative} What do the daily indexes tell us?

The mean absolute deviation averages the absolute differences between the actual values of the time series at time t and the forecast values at time t + 1.

Hotel Occupancy A small hotel has recorded the number of rooms occupied during weekdays over a period of four weeks as is shown in the table below: -{Hotel Occupancy Narrative} Calculate the seasonal (daily)indexes.

A time series is shown in the table below. a.Plot the time series.Would the linear or quadratic model fit better? b.Use the regression technique to calculate the linear trend line and the quadratic trend line.Which model fits better?

The most commonly used measures of forecast accuracy are the mean absolute deviation (MAD)and the sum of squares for forecast error (SSE).

Hotel Occupancy A small hotel has recorded the number of rooms occupied during weekdays over a period of four weeks as is shown in the table below: -{Hotel Occupancy Narrative} Find the regression trend line.

If the time series displays a gradual or no trend and no evidence of seasonal variation,exponential smoothing is not an effective as a forecasting method.

The mean absolute deviation is a measure of the average of the absolute discrepancies between the actual and the fitted values in a given time series.

If there is no obvious trend or seasonality in the time series data,and we believe that there is a correlation between consecutive residuals,the autoregressive model may be most effective as a forecasting technique.

If the time series is composed of seasonal variation and long-term trend,we can use seasonal indexes and the regression equation to forecast.

The mean absolute deviation averages the absolute differences between the actual values of the time series at time t and the forecast values at time:

Hotel Occupancy A small hotel has recorded the number of rooms occupied during weekdays over a period of four weeks as is shown in the table below: -{Hotel Occupancy Narrative} Calculate the seasonal indexes,based on the regression trend line developed in the previous question.

Which method would you recommend to your statistics professor in selecting the appropriate forecasting model if avoiding large errors is extremely important to him or her?

Quiz 20: Time-Series Analytics and Forecasting

The mean absolute deviation is the summation of the residuals divided by the sample size.

The Pyramids of Giza The Pyramids of Giza is one of the most visited monuments in Egypt.The number of visitors per quarter has been recorded (in thousands)as shown in the accompanying table: ​ ​ -{The Pyramids of Giza Narrative} Use regression analysis to develop the trend line.

Hotel Occupancy A small hotel has recorded the number of rooms occupied during weekdays over a period of four weeks as is shown in the table below: -{Hotel Occupancy Narrative} What do the daily indexes tell us?

The mean absolute deviation averages the absolute differences between the actual values of the time series at time t and the forecast values at time t + 1.

Hotel Occupancy A small hotel has recorded the number of rooms occupied during weekdays over a period of four weeks as is shown in the table below: -{Hotel Occupancy Narrative} Calculate the seasonal (daily)indexes.

A time series is shown in the table below. a.Plot the time series.Would the linear or quadratic model fit better? b.Use the regression technique to calculate the linear trend line and the quadratic trend line.Which model fits better?

The most commonly used measures of forecast accuracy are the mean absolute deviation (MAD)and the sum of squares for forecast error (SSE).

Hotel Occupancy A small hotel has recorded the number of rooms occupied during weekdays over a period of four weeks as is shown in the table below: -{Hotel Occupancy Narrative} Find the regression trend line.

If the time series displays a gradual or no trend and no evidence of seasonal variation,exponential smoothing is not an effective as a forecasting method.

The mean absolute deviation is a measure of the average of the absolute discrepancies between the actual and the fitted values in a given time series.

If there is no obvious trend or seasonality in the time series data,and we believe that there is a correlation between consecutive residuals,the autoregressive model may be most effective as a forecasting technique.

If the time series is composed of seasonal variation and long-term trend,we can use seasonal indexes and the regression equation to forecast.

The mean absolute deviation averages the absolute differences between the actual values of the time series at time t and the forecast values at time:

Hotel Occupancy A small hotel has recorded the number of rooms occupied during weekdays over a period of four weeks as is shown in the table below: -{Hotel Occupancy Narrative} Calculate the seasonal indexes,based on the regression trend line developed in the previous question.

Which method would you recommend to your statistics professor in selecting the appropriate forecasting model if avoiding large errors is extremely important to him or her?

The Pyramids of Giza The Pyramids of Giza is one of the most visited monuments in Egypt.The number of visitors per quarter has been recorded (in thousands)as shown in the accompanying table: -{The Pyramids of Giza Narrative} Use regression analysis to develop the trend line.