Science, asked by netsion2013, 18 days ago

2. The prices of two stocks vary over a 12-month period as shown below
Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Stock A 10 11 12 11 15 18 13 16 11 10 9 13
Stock B 30 33 36 32 45 49 37 48 33 30 33 39
A. Describe the variability of the stocks.
B. Which appears to be more uniform? Why?
3. Is crime rate somehow associated with age? An investigator collected the following data from five sample groups to see the relationship between the two variables:
Average age in year (X) 70 56 35 28 14
A Average crime rate (%) (Y) 28 42 35 42 48
A. Determine the regression line of crime rate on age and interpret it?
B. Estimate the % of crime rate for groups of individuals having average age 40.
C. Determine the coefficient of correlation and interpret it.

Answers

Answered by vakeelahmad2181
0

Answer:

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Answered by priyaagari1111
0

Explanation:

A.1 Forecast Calculation Methods

Twelve methods of calculating forecasts are available. Most of these methods provide for limited user control. For example, the weight placed on recent historical data or the date range of historical data used in the calculations might be specified. The following examples show the calculation procedure for each of the available forecasting methods, given an identical set of historical data.

The following examples use the same 2004 and 2005 sales data to produce a 2006 sales forecast. In addition to the forecast calculation, each example includes a simulated 2005 forecast for a three month holdout period (processing option 19 = '3') which is then used for percent of accuracy and mean absolute deviation calculations (actual sales compared to simulated forecast).

A.2 Forecast Performance Evaluation Criteria

Depending on your selection of processing options and on the trends and patterns existing in the sales data, some forecasting methods will perform better than others for a given historical data set. A forecasting method that is appropriate for one product may not be appropriate for another product. It is also unlikely that a forecasting method that provides good results at one stage of a product's life cycle will remain appropriate throughout the entire life cycle.

You can choose between two methods to evaluate the current performance of the forecasting methods. These are Mean Absolute Deviation (MAD) and Percent of Accuracy (POA). Both of these performance evaluation methods require historical sales data for a user specified period of time. This period of time is called a holdout period or periods best fit (PBF). The data in this period is used as the basis for recommending which of the forecasting methods to use in making the next forecast projection. This recommendation is specific to each product, and may change from one forecast generation to the next. The two forecast performance evaluation methods are demonstrated in the pages following the examples of the twelve forecasting methods.

A.3 Method 1 - Specified Percent Over Last Year

This method multiplies sales data from the previous year by a user specified factor; for example, 1.10 for a 10% increase, or 0.97 for a 3% decrease.

Required sales history: One year for calculating the forecast plus the user specified number of time periods for evaluating forecast performance

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