happen in the future. Forecasting will help determine to outcome of future sales projections in the business world. The Hard Rock Cafe` uses the following forecasting types: moving averages, weighted moving averages, exponential smoothing, and regression analysis. The reason that Hard Rock uses forecasting is for the long term, short term, purchasing orders, and buying supplies in their Cafés, hotels, and night clubs. The sales forecast for the company is used by the month, year or five year plans
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The Use of Dummy Variables in Regression Analysis By Smita Skrivanek, Principal Statistician, MoreSteam.com LLC What is a Dummy variable? A Dummy variable or Indicator Variable is an artificial variable created to represent an attribute with two or more distinct categories/levels. Why is it used? Regression analysis treats all independent (X) variables in the analysis as numerical. Numerical variables are interval or ratio scale variables whose values are directly comparable, e.g. ‘10 is twice
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ijcrb.webs.com INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS SEPTEMBER 2012 VOL 4, NO 5 FACTORS INFLUENCING STUDENT’S ENROLLMENT DECISIONS IN SELECTION OF HIGHER EDUCATION INSTITUTIONS (HEI’S) Farhan Mehboob Sukkur Institute of Business Administration Sukkur, Pakistan Syed Mir Muhammad Shah Sukkur Institute of Business Administration Sukkur, Pakistan Niaz A Bhutto Sukkur Institute of Business Administration Sukkur, Pakistan Abstract The study investigates the
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Augmented Dickey-Fuller Unit Root Tests How do we know when to difference time series data to make it stationary? You use the Augmented Dickey-Fuller t-statistic. Here are the various cases of the test equation: a. When the time series is flat (i.e. doesn’t have a trend) and potentially slowturning around zero, use the following test equation: Δz t = θz t −1 + α 1 Δz t −1 + α 2 Δz t − 2 + L + α p Δz t − p + a t where the number of augmenting lags (p) is determined by minimizing the Schwartz
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REGRESSION In statistics, regression analysis is a statistical process for estimating the relationships among variables. It includes many techniques for modeling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables. More specifically, regression analysis helps one understand how the typical value of the dependent variable (or 'criterion variable') changes when any one of the independent variables is varied
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total food and beverage sales for the three years of operation. The data can be found in an Excel spreadsheet (Lost Beverage and Food Sales). Perform an analysis of the sales data for the Vintage Restaurant. Prepare a report for Karen that summarizes your findings, forecasts, and recommendations. Include: a. A graph of the time series. b. An analysis of the seasonality of the data. Indicate the seasonal indexes for each month, and comment on the high and low seasonal sales months. Do the seasonal indexes
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the purpose of simple linear regression and scatter diagrams. Please provide a simple linear regression model and define each variable used. A scattered diagram is a statistic tool that is used to show the relationship between two variables. The scattered diagram is a combination of simple linear regression line that is used to fit the model in between two variables. The line that is drawn in the scatter chart is a model that is formed from the simple linear regression the data provides. The line
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Statistical Analysis Process: Generally, all of the business courses that you take are focused on answering a single question - “What can managers do to improve the performance of their organizations?” It is not sufficient to theorize that a particular business strategy will lead to improved performance. You must test the theory. The statistical analysis process is a standardized methodology for testing theories. Generally, you identify a strategy that you believe may work, you ask experts
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Koel BANERJEE, Sahil BIHARI, Rong TIAN, Jean-Baptiste VARNIER, Dmitry YATSENKO House Prices Analysis in the DFW Area Report prepared for M. Sam Horton HEC PARIS MBA PROGRAM FALL 2014 FINAL TEAM PROJECT 0 Statistics and Business Analytics, FALL 2014 ES-1, Grp 7: Koel BANERJEE, Sahil BIHARI, Rong TIAN, Jean-Baptiste VARNIER, Dmitry YATSENKO This report summarizes the statistical analysis performed in relation to the sale of houses in the Dallas Fort Worth (DFW) area, which includes
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A Meta-Analysis of the Economic Impacts of Climate Change Policy in the United States Adam Rose* and Noah Dormady** This paper provides a meta-analysis of a broad set of recent studies of the economic impacts of climate change mitigation policies. It evaluates the infiuences of the impacts of causal factors, key economic assumptions and macroeconomic linkages on the outcome of these studies. A quantité regression analysis is also performed on the meta sample, to evaluate the robustness of
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