×

### Let's log you in.

or

Don't have a StudySoup account? Create one here!

×

or

## MGS 3100, week 4 notes

by: Tricia Williams

39

0

4

# MGS 3100, week 4 notes MGS 3100

Tricia Williams
GSU
GPA 3.86

Get a free preview of these Notes, just enter your email below.

×
Unlock Preview

These notes cover what will be in the next exam
COURSE
Buisness Analysis
PROF.
Mark Sweatt
TYPE
Class Notes
PAGES
4
WORDS
KARMA
25 ?

## Popular in Managerial Science

This 4 page Class Notes was uploaded by Tricia Williams on Sunday July 3, 2016. The Class Notes belongs to MGS 3100 at Georgia State University taught by Mark Sweatt in Summer 2016. Since its upload, it has received 39 views. For similar materials see Buisness Analysis in Managerial Science at Georgia State University.

×

## Reviews for MGS 3100, week 4 notes

×

×

### What is Karma?

#### You can buy or earn more Karma at anytime and redeem it for class notes, study guides, flashcards, and more!

Date Created: 07/03/16
MGS 3100 in-class notes (6/27/2016) Averaging techniques continue Simple exponential smoothing:- Looks at two things when forecasting, the actual sales and the forecast. The actual sales from the previous period are multiplied by the alpha, which is given, and one minus alpha multiplies the previous period forecast. The two amounts are then added together to give the forecast for the next period. Additionally, the second period forecast uses the naïve method of forecasting. Fitting a Trendline Regression: Tells if Y and X are related and if so, how closely related are they. Simple Regression:- Uses one variable to forecast the dependent variable Y ( Y=intercept + variable (coefficient)) Multiple Regression: Uses more than one variable or multiple independent variable to forecast the dependent variable Y. Y=Intercept + variable (coefficient) + variable (coefficient) + variable (coefficient)……………. This model is use when there is a trend in the data collected about the item to be forecasted. The above technique is evaluated by using the same evaluation criteria as averaging techniques plus R-squared. Regression equation= ( Y=intercept + variable (coefficient)) Mean shoe size = average of the shoe size Deviation from the mean = actual shoe size-mean shoe size SS= sum of squared deviations Degrees of freedom (df)- is the variance you are allow to have from forecasting P-value:- Tells which variable is most significant in relation to what is being forecast. (The smaller the p-value, the more significant). Significant of F:- How reliable is the model, the smaller the figure, the better. If it is not less than 0.1, then the correlation is not meaningful. Some truth about forecasting 1. What happen in the past is more likely to happen in the future. 2. Forecast accuracy increases for shorter time frames 3. Combined forecasting is more accurate than forecasting done on an individual basis. 4. Forecasts are hardly ever accurate. Formulas SS= df * MS 2 R-Square= SS/SST or (multiple R) Multiple R= Square root of R-Square Standard error= Square root of MS of the (residual) Total degrees of freedom (n-1) where n is the observation total Total df for regression = the number of variables=K Total df for residual = (n-K-1) Anova:- Analysis of Variance MGS 3100 in-class notes (6/29/2016) Trend and Seasonal Index/Seasonality All seasonality factors/indices must total to (4) Deseasonalized sales:- It is moving the seasonality from the data. (Actual sales/seasonalized index) Reseasonalized forecast (seasonalized) :- Making the final forecast. (deseasonalized forecast x seasonalized index (SI)) Forecasting: Decomposition of the trend and seasonality Moving average:- Take the average of the actual sales of two period above, the current period, and one period below. Centered average:- Take the average of the moving average current period and the immediate period that follow. Raw Indices: (Actual sales/centered average) Seasonalized index= averaging the raw indices for the different years (Year 1, year 2, year 3, year 4 etc.) Predicted sales (y-hat) are transferred from the output sheet. Y-Y hat error (Bias):- Sales (Y) - Predicted sales (Y-hat) 2 Error squared (Y-Y-hat) Finding the seasonalized forecast of a specific quarter Sales trend:- This is computed by first finding the time period for the specified quarter for which you need to find the seasonalized forecast (eg. Q1, 2013) Always begin with the beginning quarter as period one. You then plug the specified time period number into the sales trend equation, which will give the deseasonalized forecast. Seasonalized forecast: To find the seasonalized forecast is (seasonalized index for the specified quarter, in this case is Q1 multiplied by the deseasonalized forecast).

×

×

### BOOM! Enjoy Your Free Notes!

×

Looks like you've already subscribed to StudySoup, you won't need to purchase another subscription to get this material. To access this material simply click 'View Full Document'

## Why people love StudySoup

Jim McGreen Ohio University

#### "Knowing I can count on the Elite Notetaker in my class allows me to focus on what the professor is saying instead of just scribbling notes the whole time and falling behind."

Kyle Maynard Purdue

#### "When you're taking detailed notes and trying to help everyone else out in the class, it really helps you learn and understand the material...plus I made \$280 on my first study guide!"

Bentley McCaw University of Florida

Forbes

#### "Their 'Elite Notetakers' are making over \$1,200/month in sales by creating high quality content that helps their classmates in a time of need."

Become an Elite Notetaker and start selling your notes online!
×

### Refund Policy

#### STUDYSOUP CANCELLATION POLICY

All subscriptions to StudySoup are paid in full at the time of subscribing. To change your credit card information or to cancel your subscription, go to "Edit Settings". All credit card information will be available there. If you should decide to cancel your subscription, it will continue to be valid until the next payment period, as all payments for the current period were made in advance. For special circumstances, please email support@studysoup.com

#### STUDYSOUP REFUND POLICY

StudySoup has more than 1 million course-specific study resources to help students study smarter. If you’re having trouble finding what you’re looking for, our customer support team can help you find what you need! Feel free to contact them here: support@studysoup.com

Recurring Subscriptions: If you have canceled your recurring subscription on the day of renewal and have not downloaded any documents, you may request a refund by submitting an email to support@studysoup.com