Problems and Questions

briefly explain the meaning of R-squ bed. A quantify series analysis of demand tends to go forth In a higher R-squared than wiz apply cross-sectional selective information. wherefore do you think this Is the case? R-squared measures the goodness of see of a regression comparison. A era series analysis of demand tends to expiration in a higher necessary than one using cross-sectional info because data is being gathered at multiple periods of time as contend to one period of time when using cross-sectional data. II.What is the identification trouble? What force-out will this problem have on the regression estimates off demand draw? Explain. The identification problem occurs when there Is an inability In the principle to Identify the opera hat estimate of values of one or more variables In regression. This problem effects regression estimates of a demand manoeuver because there is a simultaneous faulting of both the supply and demand, which results in one-sided r esults. Ill. A. Why are manufacturers new revisions, endogens great(p) goods, an appropriate leading index?They are an appropriate Indicator because they are commitments that plant that economic activity will concord place In the future. B. Why Is the exponent of Industrial production an appropriate synchronous Indicator? The Index of Industrial production Is an appropriate coincident indicator because it provides information about the current state of the economy. C. Why is the average prime rate aerated by banks an appropriate lagging indicator? Its an appropriate lagging indicator because changes in the prime rate generally tip changes in the rest of the economy.IV. You have been asked to realize a forecast for your compacts product, bottled irrigate. Discuss the sweet of Information you would look for In order to make this forecast. An effective forecast for bottled water would Include sales revenue, marketing, competition, Seibel issues that may climb up in the futu re, and information about the organize demographic. V. One of the most difficult tasks in regression analysis is to obtain the data suitable for quantitative studies of this kind.Suppose you are essay to estimate the demand for home piece of furniture. signify kinds of variables that could be used to represent the avocation factors, which are believed to affect the demand for any(prenominal) product. Do you anticipate any clog in securing such data? Explain. Determinants of study for Furniture Suggested Variables to use in simple regression Analysis damage Prices set for furniture at competing companies Tastes & Preferences % of people who like modern, rustic, traditional, contemporary, country, etcetera Hypes of furniture Price of related products Price of accent Items (blinds, pillows, rugs) Income Average Income of buyers Cost or availability of character reference % of people who leveraging furniture with cash or credit Number of buyers of sales per year early exp ectations Availability of products, future income of buyers Other come-at-able factors Seasonal sales I do not see any problem securing this data. Most of this Information can be maker of a leading snitch of low-calorie microwaveable food estimated the following emend equation for its product using data from 26 supermarkets around the country for the month of April.