Stat 160 Prequiz over Section 8.1, 8.2 and Chi_Squared Goodness of Fit Test

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1. In terms of hypotheses testing of H0 versus HA, a Type I error occurs if

HA is rejected when HA is true.
H0 is accepted when HA is true.
H0 is accepted when H0 is true.
H0 is rejected when H0 is true.
2. Usually Type I error is regarded as the more serious of the two errors.

Neither true nor false.
3. The chi-squared goodness of fit test tests a hypothesis about the probabilities (distribution) of a random variable.

No, it's the badness of fit test.
4. Suppose we had a coin and we wanted to test (via the goodness of fit test) that it is fair; i.e., the probability of a head is 1/2. Suppose we flip it 200 times and observe 91 heads. What is the expected frequency of heads which would be used in the goodness of fit test?