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1 in the example of this chapter the coefficient of the dummy variable for restaurants identified as services-eating
do the partial f-statistic and t-statistics have to agree for example consider adding two explanatory variables w and u
consider testing the null hypothesis h0 b3 0 in a multiple regression with k 5 explanatory variablesa how could you
a modeler has omitted an explanatory variable that is related to the response but not correlated with the explanatory
many economic relationships are characterized by diminishing marginal returns these occur when the effects of
a regression was built to predict the dollar value of a customer transaction a three-level categorical variable
1 an explanatory variable is skewed whereas the response is bell-shaped why is it not possible for this variable to
a manager conducted a small survey of office employees to find out how many play the office pool that selects the
28 the interval from the smallest to largest amounts sold during the eight shifts in exercise 37 is 1889 to 4592 if
most of the stock trades at an office that handles over-the-counter retail stock sales are fairly small but sometimes a
the manager of a convenience store tracked total sales during a small sample of eight recent daytime shifts an
1 a 95 confidence interval for the mean of a samplenbsp of positive numbers can include negative values if the sample
1 a printout in the back of a market report summarized sales in retail outlets with two intervals but did not label
1 a retailer has data on sales in its stores yesterday it would like a range that has a 50 chance of covering the sales
a taste test has customers tasnte two types of cola drinks and asks which is preferred an analyst then finds the sample
1 an analyst decided to use either the 95 t-interval for the mean or the corresponding 95 interval for the median
an investor scanned the daily summary of the stock market in the wall street journal she found 12 stocks whose return
in looking over sales generated by 15 offices in his district a manager noticed that the distribution of sales was
1 fit the saturated regression of the number of projects per 1000 on the variables defined in the next 33 columns of
1 the stepwise model table 6 includes the explanatory variable sq temp deviation the square of the difference between
1 perform a two-way analysis of variance of rating by vehicle type and manufacturer use economy cars from the united
1 the structure of these data resembles the structure of the data in the pricing example but there are differencesa
the analysis shown here uses a balanced experiment with equal numbers of observations for each pairing of the factors
1 what happens to the profile plot in figure 1 if we reverse the rows and columns of the data let price partition
1 whats the estimated value from the anova regression given by the slopes in table 4 for the change in sales in the