A (42%) B (42%) C (16%)
Most preferred Pepsi Coke Classic New Coke
Second choice Coke Classic New Coke Pepsi
Least preferred New Coke Pepsi Coke ClassicAs the table shows, 42 percent of consumers are “type A,” whose top
preference is Pepsi, followed by Coke Classic and New Coke. Are these
preferences consistent with the information in part (a)? What do you
predict would be the result of a blind taste test between Coke Classic
and New Coke?
c. From the information in part (b), what brand strategy would you
recommend to Coca-Cola’s management? What additional
information about consumer preferences might be useful?- A financial analyst seeks to determine the relationship between the return
on PepsiCo’s common stock and the return on the stock market as a whole.
She has collected data on the monthly returns of PepsiCo’s stock and the
monthly returns of the Standard & Poor’s stock index for the last five years.
Using these data, she has estimated the following regression equation
Here, returns are expressed in percentage terms. The t-values for the
coefficients are 2.78 and 3.4, respectively, and the equation’s R^2 is .28.
a. Do the respective coefficients differ significantly from zero?
b. The value of R^2 seems quite low. Does this mean the equation is
invalid? Given the setting, why might one expect a low R^2?
c. Suppose the S&P index is expected to fall by 1 percent over the next
month. What is the expected return on PepsiCo’s stock?- To what extent do you agree with the following statements?
a. The best test of the performance of two different regression equations
is their respective values of R^2.
b. Time-series regressions should be run using as many years of data as
possible; more data means more reliable coefficient estimates.
c. Including additional variables (even if they lack individual
significance) does no harm and might raise R^2.
d. Equations that perform well in explaining past data are likely to
generate accurate forecasts. - A study of cigarette demand resulted in the following logarithmic
regression equation:
1 2.07) 1 1.05 2 1 4.48 2 1 5.2 2
log 1 Q 2 2.55.29 log 1 P 2 .09 log 1 Y 2 .08 log 1 A 2 .1W.RPep.06.92RS&P.170 Chapter 4 Estimating and Forecasting Demandc04EstimatingandForecastingDemand.qxd 9/5/11 5:49 PM Page 170