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Respond to the following 2 initial post with a short response:
Discussion 1 topic- Discuss the business uses of time series forecasting.
Initial Post (Tim)- In the textbook page 861, it describes the definition for time series. It is a sequence of observations on a variable measured at successive points in time over successive periods of time. The measurement may be taken every hour, day, week, month, or year, or year, or at any other regular interval. The pattern of the data is an important factor in understanding how the time series has behaved in the past. When using forecasting it is an approach that uses the most recent week’s sales volume as the forecast for the next week. Your decision to use forecasting can be determined by how accurate your forecasting is. What determines the accuracy is the forecast error. Forecast Error = Actual Value – Forecast. There are 3 different methods to finding the error. The first is mean absolute error, the second is mean squared error, and lastly the mean absolute percentage error. Like the textbook states about choosing the correct method, “Measures of forecast accuracy are important factors in comparing different forecasting methods, but we must be careful not to rely upon them too heavily. Good judgement and knowledge about business conditions that might affect the forecast also have to carefully considered when selecting methods”. Thanks for your time.

Discussion 2 topic- Discuss the two different uses of Chi-Square analysis
Initial Post (Mukhalad)- Hello,
A Chi-square test is used to assess for correlation between two categorical variables. The statistical technique is used to determine if the difference between observed data and expected data is caused by the relationship between the variables being examined. The test is vital in understanding and interpreting the relationship between two categorical variables. Therefore, chi-square analysis can be applied in evaluating the divergence of observed results from those anticipated on the hypothesis of equal probability. Alternatively, a chi-square can be used to assess if the divergence of observed results from the expected is from a normal distribution. For example, a manager may classify his or her employees in particular categories, which would be considered a normally distributed categorization. If a study is conducted and observations made, a chi-square test can be done to determine the divergence between the variables.
Anderson, D. R., Sweeney, D.J., Williams, T. A., Camm, J. D., & Cochran, J. J.(2019). Statistics for Business & Economics (14th ed.). Cengage Learning US.