Author: Anonymous

Suppose I reject a hypothesis at the 

When another predictor is added to a model, the unadjusted R2 can NEVER decrease.

Which of these measures is robust to (not affected much by) outliers? Select all that apply

The probability model below describes the number of repair calls that an appliance repair shop may receive during an hour   Repair calls 0 1 2 3 Prob 0.10 0.30 0.40 0.20   We have 2 employees on staff at the moment.  What’s the chance we need to call in another employee this hour to fulfill demand? (1 employee can handle 1 call)

e-grocers sell groceries over the internet.  Customers enter their orders, pay by credit card, and receive delivery by truck.  A potential e-grocer analyzed the market and determined that the average order would have to exceed $85 if the e-grocer were to be profitable.  To determine whether an e-grocery would be profitable in one large city, she offered the service and recorded the size of the order for a random sample of 85 customers.   sample mean = $89.22 sample sd = $17.30 Suppose you ran all the numbers and got a p-value of 0.014, what is your conclusion at the 5% significance level?

A model was fit to predict the Calories based on the sugars (g/cup) and Company.  There were 3 Companies (G = General Mills, K = Kellogg’s , and Q = Quaker). > summary(mod) Call:lm(formula = Calories ~ Sugars + Company, data = Cereal) Residuals:Min                    1Q            Median           3Q                  Max -39.697        -25.414          -1.459          16.559             55.349 Coefficients:                        Estimate        Std. Error        t value           Pr(>|t|) (Intercept)         85.3035          12.5365          6.804           3.2e-07 ***Sugars                4.3146            0.9556          4.515           0.000121 ***CompanyK          6.6755          11.2324          0.594           0.557443 CompanyQ         5.6221          13.5345          0.415           0.681266 —Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 27.41 on 26 degrees of freedomMultiple R-squared: 0.4442, Adjusted R-squared: 0.3801 F-statistic: 6.926 on 3 and 26 DF, p-value: 0.001405 Based on this output, which company had the HIGHEST  caloric content after Sugars were accounted for?

Given a relation: Student (SID, SName, major, age, city). The data file contains 1000 pages and each page contains 100 tuples. Suppose there is a B+tree index on city and it is unclustered. There are 100 different cities stored in the table and uniform distribution is assumed for the values. The index file contains 20 pages. Given the query: Select * from Student where city=”Rochester”, which of the query plan is more efficient?

A researcher wants to know whether drinking caffeine before a test changes the average number of errors college students make on a proofreading task. The population of students who do not consume caffeine before the task makes a mean of 12 errors. What is the most appropriate null hypothesis?

What measures and quantifies the likelihood of obtaining a specific sample from a specific population?

What p-value is statistically significant?