moving average. [3] d) Plot the original data and the three forecasts on the same graph. Which forecast smoothes the data the most? Which forecast responds to change the best? [4] Problem 2 [4] Given the following data‚ use exponential smoothing (( = 0.3) to develop a demand forecast. Assume the forecast for the initial period is 5. |Period 1 2 3 4 5 6 | |Demand 7 9 5 9 13 8
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n Some firms use subjective methods n Seat-of-the pants methods‚ intuition‚ experience n There are also several quantitative techniques n Moving averages‚ exponential smoothing‚ trend projections‚ least squares regression analysis` © 2009 Prentice-Hall‚ Inc. 5–2 1 9/5/14 Introduction n Eight steps to forecasting : 1. Determine the use of the forecast—what objective are we trying to obtain? 2. Select the items or quantities that are to be forecasted 3. Determine the time horizon
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TO DETERMINE THE LEVEL OF CUSTOMER SATISFACTION IN DAYSTAR UNIVERSITY CAFETERIA A project submitted to the School of Business and Economics in partial fulfillment of the requirement for the course Research Methodology BUS 213X Daystar University Nairobi‚ Kenya By Mark Reuben Gathigi 08-1064 November 2012 DECLARATION In presenting‚ this research in partial fulfillment of the requirements of the course code BUS 213X – Research Methodology from Daystar University‚ I declare that this
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upon a time there was no zero. Of course people knew if they had nothing‚ but there was no mathematical notation for it. Zero was independently invented only three times. The first recorded zero is attributed to the Babylonians in the 3rd century BC. A long period followed when no one else used a zero place holder. But then the Mayans‚ halfway around the world in Central America‚ independently invented zero in the fourth century CE. The final independent invention of zero in India was long debated
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Coke often rejected it anyway because of its aspartame-sweetened aftertaste. “What we were seeing before Zero launched was that more and more younger people were interested in no-calorie beverages but weren’t going to sacrifice taste‚” Bayne said. “So when they got interested in no-calorie‚ they were like‚ ‘Forget it‚ I’m not going to Diet Coke.’” Testing showed that the name “Coke Zero” would be an effective way to sell a low-calorie cola to men without using the word “diet.” And advances
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Question 1: Logarithms (i) The interpretation of the slope coefficient in the model Yi = β0 + β1 ln(Xi ) + ui is as follows: (a) a 1% change in X is associated with a β1 % change in Y. (b) a 1% change in X is associated with a change in Y of 0.01 β1 . (c) a change in X by one unit is associated with a β1 100% change in Y. (d) a change in X by one unit is associated with a β1 change in Y. (ii) The interpretation of the slope coefficient in the model ln(Yi ) = β0 + β1 Xi + ui is as follows: (a) a
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Due in class Feb 6 UCI ID_____________________________ MultipleChoice Questions (Choose the best answer‚ and briefly explain your reasoning.) 1. Assume we have a simple linear regression model: . Given a random sample from the population‚ which of the following statement is true? a. OLS estimators are biased when BMI do not vary much in the sample. b. OLS estimators are biased when the sample size is small (say 20 observations)
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PEARSON PRODUCT MOMENT CORRELATION COEFFICIENT Definition It is the measure of the linear correlation between two variables X and Y It is the measure of the strength of a linear association between two variables and is denoted by r. It tells you how strong the linear correlation is for paired numeric data e.g. height and weight. The Pearson correlation coefficient‚ r‚ indicates how far away all these data points are to this line of best fit. Development It was the imagination and idea of Sir Francis
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CONDUCT OF RESEARCH The following is the institutional format used by FC in conducting research: A. Parts Research shall consist of the following parts where applicable: 1. Title Page 2. Approval Sheet 3. Abstract 4. Dedication 5. Acknowledgment 6. Table of Contents 7. List of Tables 8. List of Figures 9. List of Appendices 10. Chapter 1 The Problem and its Background 11. Chapter 2 Review of Related Literature and Studies 12. Chapter 3 Methods‚ Procedures‚ and
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When to use each test? What is the sig value? Whether or not it is significant? Read output and tell you what that value means (significant or not) One sample: given population value and compare your sample to that population Know if its significant: analyze compare means‚ one sample t-test Independent sample t-test: lab one against lab five Two independent groups (compare their means) Significance use twotail Define the correct groups: Paired sample: only care about one lab and you look at before
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