I want real data set about nonlinear regression and the error follows autoregressive moving average time...
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I want real data set about nonlinear regression and the error
follows autoregressive moving average time...
When using autoregressive regression analysis to find a best-fitting line to a set of time series...
When using autoregressive regression analysis to find a best-fitting line to a set of time series data with trend, we should use time period as the independent variable. true or false
Your time series data are as follows. 0.513 -0.396 -0.85 -1.73 0.127 0.403 0.959 1.498 1.349...
Your time series data are as follows.
0.513 -0.396 -0.85 -1.73 0.127 0.403 0.959 1.498 1.349 -0.186 1.082
-0.92 -1.504 0.135 -0.271 0.726 0.702 0.769 0.854 1.498
For these data, plot the times series, plot the acf, and get the
acf function numerically. Consider this as the training set.
Please answer the following.
Your time series data are as follows 0.513-0.396-0.85-1.73 0.127 0.403 0.959 1.498 1.349-0.186 1.082-0.92 -1.504 0.135-0.271 0.726 0.702 0.769 0.854 1.498 For these data, plot the times...
#1 Attached is an Excel spreadsheet containing the exponential smoothing, moving average, and quarterly regression analyses of the data set in problem #23 in Chapter 8. Use the Excel spreadsheet to a...
#1 Attached is an Excel spreadsheet containing the exponential smoothing, moving average, and quarterly regression analyses of the data set in problem #23 in Chapter 8. Use the Excel spreadsheet to answer the following questions. #1.1 which of the nine exponential smoothing models in columns J through R would you use to forecast Value for time-13, and why would you use it? (5 points) #1.2 what is the exponential smoothing forecast of Value for time-13 for (Show your work.) (5...
Your time series data are as follows. 1.447 1.298-0.682 -0.575 0 -0.287-0.221 0.15 0.023 0.899 1.886...
Your time series data are as follows. 1.447 1.298-0.682 -0.575 0 -0.287-0.221 0.15 0.023 0.899 1.886 -0.701 -1.107-0.788 -1.595 -0.275-0.006-0.577 -0.706 -1.475 For these data, plot the times series, plot the acf, and get the acf function numerically. Consider this as the training set. Please answer the following. Part a) The serial correlations of lags 1,2,3 are: Part b) Your holdout set for observations at times 21 to 25 are: -0.946 -1.413 0.416 0.965 0.692 Next you will apply the...
1. Does a moving average forecast become more or less responsive to changes in a data...
1. Does a moving average forecast become more or less responsive to changes in a data series when more data points are included in the average? 2. If a forecast is too high when compared to an actual outcome, will that forecast error be positive or negative? 3. Are quantitative forecasting models generally used for shorter-term or longer-term decision making when compared to qualitative approaches? 4. The South Florida Water Management District (SFWMD) must develop a linear regression model that...
Assume you are analyzing a time series of 12 observations. Using a 3-period moving average, you...
Assume you are analyzing a time series of 12 observations. Using a 3-period moving average, you successfully calculate the Mean Absolute Error (MAE), Mean Square Error (MSE), and Mean Absolute Percentage Error (MAPE) for each forecasted time period. You then sum the error calculations for each time period for each of the three error calculation techniques respectively. You end up with: MAE 53.5, MSE 547.25, and MAPE 44.15%. To complete your error calculation and compare the accuracy of the 3-period...
7. Suppose a data set of 150 observations (N =150) was analyzed using OLS to examine...
7. Suppose a data set of 150 observations (N =150) was analyzed using OLS to examine the factors that influence college grade point average (GPA). The regression results are as follows: log(colGPA)=5.5+0.5*hsGPA+0.02*ACT −0.08*skipped. (0.5) (0.1) (0.01) (0.03) where the number in the parenthesis is the corresponding standard error. You want to test the following null hypothesis: the coefficient estimate for ACT=0. What is the t statistic? Suppose the critical value=2.5, would you reject the null hypothesis?
Suppose a data set of 150 observations (N =150) was analyzed using OLS to examine the factors tha...
Suppose a data set of 150 observations (N =150) was analyzed using OLS to examine the factors that influence college grade point average (GPA). The regression results are as follows: log(colGPA)=5.5+0.5*hsGPA+0.02*ACT −0.08*skipped (0.5) (0.1) (0.01) (0.03) where the number in the parenthesis is the corresponding standard error. You want to test the following null hypothesis: the coefficient estimate for ACT=0. What is the t statistic? Suppose the critical value=1.6, would you reject the null hypothesis?
Suppose data about the average number of hours people spend on social media websites at work...
Suppose data about the average number of hours people spend on social media websites at work is randomly collected for 5 days: 4, 4.5, 2.5, 2, 6 A.) If we assume this population is normally distributed, construct an 80% confidence interval for the population average amount of time people spend on social media websites at work. B.) Suppose I want to know more about how workers spend their time throughout the day. I want to test the claim that people...
hello this is about linear regression i want answer the question using R write the results...
hello
this is about linear regression
i want answer the question using R
write the results and command of R
A marketing researcher studied annual sales of a product that had been introduced 10 years ago. The data are as follows, where X is the year (coded) and Y is sales in thousands 1 VI X;: 2 135 3 162 4 178 5 221 6 232 5 7 283 6 8 306 7 9 374 8 10 395 9 98...
Your time series data are as follows.
0.513 -0.396 -0.85 -1.73 0.127 0.403 0.959 1.498 1.349 -0.186 1.082
-0.92 -1.504 0.135 -0.271 0.726 0.702 0.769 0.854 1.498
For these data, plot the times series, plot the acf, and get the
acf function numerically. Consider this as the training set.
Please answer the following.
Your time series data are as follows 0.513-0.396-0.85-1.73 0.127 0.403 0.959 1.498 1.349-0.186 1.082-0.92 -1.504 0.135-0.271 0.726 0.702 0.769 0.854 1.498 For these data, plot the times...
#1 Attached is an Excel spreadsheet containing the exponential smoothing, moving average, and quarterly regression analyses of the data set in problem #23 in Chapter 8. Use the Excel spreadsheet to answer the following questions. #1.1 which of the nine exponential smoothing models in columns J through R would you use to forecast Value for time-13, and why would you use it? (5 points) #1.2 what is the exponential smoothing forecast of Value for time-13 for (Show your work.) (5...
Your time series data are as follows. 1.447 1.298-0.682 -0.575 0 -0.287-0.221 0.15 0.023 0.899 1.886 -0.701 -1.107-0.788 -1.595 -0.275-0.006-0.577 -0.706 -1.475 For these data, plot the times series, plot the acf, and get the acf function numerically. Consider this as the training set. Please answer the following. Part a) The serial correlations of lags 1,2,3 are: Part b) Your holdout set for observations at times 21 to 25 are: -0.946 -1.413 0.416 0.965 0.692 Next you will apply the...
Assume you are analyzing a time series of 12 observations. Using a 3-period moving average, you successfully calculate the Mean Absolute Error (MAE), Mean Square Error (MSE), and Mean Absolute Percentage Error (MAPE) for each forecasted time period. You then sum the error calculations for each time period for each of the three error calculation techniques respectively. You end up with: MAE 53.5, MSE 547.25, and MAPE 44.15%. To complete your error calculation and compare the accuracy of the 3-period...
hello
this is about linear regression
i want answer the question using R
write the results and command of R
A marketing researcher studied annual sales of a product that had been introduced 10 years ago. The data are as follows, where X is the year (coded) and Y is sales in thousands 1 VI X;: 2 135 3 162 4 178 5 221 6 232 5 7 283 6 8 306 7 9 374 8 10 395 9 98...
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