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In building a confidence interval for ATE in experimental data, which of the following is not required?


A) The average outcome of the treated group
B) The average outcome of the control group
C) The number of subjects in the control group
D) Null hypothesis proposed value of the ATE

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Let Y1i be the output for factory i when it receives a new machine, and let Y0i be the output for factory i when it does not receive a new machine. Also let Yi be the realized output for factory i and let Di be a binary variable that equals one if factory i actually received a new machine. If the company's headquarters randomly assigns new machines to a subset of the company's factories, this ensures:


A) E(Yi|Di = 1) = E(Y1i - Y0i)
B) E(Yi|Di = 1) - E(Yi|Di = 0) = E(Y1i - Y0i)
C) E(Yi|Di = 0) - E(Yi|Di = 1) = E(Y1i - Y0i)
D) E(Yi|Di = 1) = E(Yi|Di = 0)

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A treatment effect is:


A) an unbiased estimate.
B) the change in the outcome resulting from variation in the treatment.
C) the variation in the treatment.
D) the different treatments among treated and control groups.

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As long as our sample is large enough it will be the case that the average outcome for the untreated group should have what distribution?


A) Normal
B) Skewed distribution
C) T-distribution
D) The same as the underlying population distribution

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Randomizing the treatment in an experiment facilitates all of the following conclusions except for what?


A) ETT = ATE
B) Selection Bias = 0
C) ATE = 0
D) None of the answers is correct.

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Suppose you want to build a 90% confidence interval for the ATE when the average outcome for the treated (55 subjects) is 12, with a sample standard deviation of 4, while the average outcome for the control (65 subjects) is 10, with a sample standard deviation of 6. Which of the following would be the proper confidence interval?


A) 0 ± 1.96 (4255+6265) \left( \sqrt { \frac { 4 ^ { 2 } } { 55 } + \frac { 6 ^ { 2 } } { 65 } } \right)
B) 0 ± 1.65 (4255+6265) \left( \sqrt { \frac { 4 ^ { 2 } } { 55 } + \frac { 6 ^ { 2 } } { 65 } } \right)
C) 2 ± 1.65 (4255+6265) \left( \sqrt { \frac { 4 ^ { 2 } } { 55 } + \frac { 6 ^ { 2 } } { 65 } } \right)
D) 0 ± 1.96 ((55+65) ( \sqrt { ( 55 + 65 } )

Correct Answer

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Which of the following limits the use of experimental data in business settings/applications?


A) The software to handle the analysis of experimental data is prohibitively expensive.
B) Experimental data is often too large for businesses to handle.
C) Conducting experiments relevant for business questions are often not feasible.
D) Most business applications do not involve questions centered on causality.

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Suppose you wanted to determine if you should reject the null hypothesis that running a playing fast tempo (as opposed to slow) music in your store decreases sales by $100 on average. On 65 randomly selected days with fast tempo music on the average store sales is $2,345 with a sample standard deviation of 45, while on 75 randomly selected days with slow tempo music on the average store sales is $2,555, with a sample standard deviation of 65. What would be the proper t-stat for this hypothesis test?


A) 2345−255545265+65275\frac { 2345 - 2555 } { \sqrt { \frac { 45 ^ { 2 } } { 65 } + \frac { 65 ^ { 2 } } { 75 } } }
B) 2345−2555−10045265+65275\frac { 2345 - 2555 - 100 } { \sqrt { \frac { 45 ^ { 2 } } { 65 } + \frac { 65 ^ { 2 } } { 75 } } }
C) 2345−2555+10045265+65275\frac { 2345 - 2555 + 100 } { \sqrt { \frac { 45 ^ { 2 } } { 65 } + \frac { 65 ^ { 2 } } { 75 } } }
D) 2345−2555452+652\frac { 2345 - 2555 } { \sqrt { 45 ^ { 2 } + 65 ^ { 2 } } }

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The critical hurdle with measuring treatment effects is that:


A) our subjects cannot be both untreated and treated at the same time.
B) we have selection bias.
C) it's always equal to the effect of the treatment on the treated.
D) it's hard to have a truly random treatment assignment.

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What is the most critical hurdle using nonexperimental data must overcome?


A) Lack of the random assignment of the treatment
B) Measuring outcomes effectively
C) Overcoming high attrition rates
D) Removing measurement error

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Which of the following will yield nonexperimental data?


A) A clinical trial for determining the efficacy of a new drug
B) Crop yields from plots subject to different types of fertilizers
C) Investment performance over the last ten years of several portfolio managers
D) None of the answers is correct.

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As long as our sample is large enough, it will be the case that the average outcome for the treated group should have what distribution?


A) Normal
B) Skewed distribution
C) T-distribution
D) The same as the underlying population distribution

Correct Answer

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Why should we expect to estimate the treatment effect of price on quantity sold to be so difficult in nonexperimental data?


A) Firms are not likely to keep detailed records of their prices.
B) Obtaining actual quantity information from sales records is difficult.
C) Firms vary their prices strategically in response to expectations of the resulting sales.
D) Sales taxes create wedges between prices paid and revenue received by the firm.

Correct Answer

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Something that is administered to members of at least one participating group is known as the:


A) treatment.
B) treatment effect.
C) potential outcome.
D) average treatment effect.

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Which of the following fields is likely to experience nonexperimental data more frequently than experimental data?


A) Business
B) Chemistry
C) Pharma
D) Psychology

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In trying to measure the "treatment effect" of taking Tylenol on reducing your "next day's temperature from today", and given the fact that you only take Tylenol when you're feeling sick, which of the following conditions are likely?


A) ETT > ATE
B) Selection Bias > 0
C) Selection Bias < 0
D) ETT = ATE

Correct Answer

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The government runs an experiment where a random sample of 200 adults over 40 get a 5% tax cut and a random sample of 200 adults under 40 get no tax cut. Their results show that spending, on average, increased 8% with a 5% tax cut. They conclude that a 5% tax cut for all adult Americans will increase spending by 8%. Why is this logic flawed?


A) The effect of the treatment on the treated may not be the average treatment effect.
B) A 5% tax cut for all Americans suffers from selection bias.
C) The measured effect of the treatment on the treated may be biased.
D) The logic is not flawed.

Correct Answer

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Suppose you want to build a 95% confidence interval for the ATE when the average outcome for the treated (55 subjects) is 12, with a sample standard deviation of 4, while the average outcome for the control (65 subjects) is 10, with a sample standard deviation of 6. Which of the following would be the proper confidence interval?


A) 0 ± 1.96 (4255+6265) \left( \sqrt { \frac { 4 ^ { 2 } } { 55 } + \frac { 6 ^ { 2 } } { 65 } } \right)
B) 0 ± 2.58 (4255+6265) \left( \sqrt { \frac { 4 ^ { 2 } } { 55 } + \frac { 6 ^ { 2 } } { 65 } } \right)
C) (12 - 10) ± 1.96 (4255+6265) \left( \sqrt { \frac { 4 ^ { 2 } } { 55 } + \frac { 6 ^ { 2 } } { 65 } } \right)
D) 0 ± 1.96 ((55+65) ( \sqrt { ( 55 + 65 } )

Correct Answer

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If you have a sufficiently large sample that was randomly drawn from your target population with a randomly assigned treatment then all of the following conditions hold except for what?


A) Selection bias = 0
B) Difference in average outcomes for treated and control groups is an unbiased estimate of the ATE.
C) The distribution for the difference in average outcomes for treated and control groups will be distributed normally.
D) None of the answers is correct.

Correct Answer

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The change in the outcome resulting from variation in the treatment is known as the:


A) selection bias.
B) random treatment.
C) treatment effect.
D) effect of the treatment on the treated.

Correct Answer

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