1. The statistical inference error in which the null hypothesis is rejected, even though it is true, is known as __________. [2 pts] 2. Sometimes known as the "hypothesis of no effect", the assumed hypothesis that we construct experiments to statistically prove, or disprove, is known as __________. [2 pts] 3. When a statistician refers to the phrase, "level of significance", they are typically referring to a concept known as __________. [2 pts] 4. The probability of committing a Type II Error is expressed as what? (hint: a Greek letter). [2 pts] 5. The experimental design that makes two observations (samples) from a single population, or single machine, etc, for statistical comparison is known as __________. [2 pts]
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Step 1: The statistical inference error in which the null hypothesis is rejected, even though it is true, is known as a Type I Error. Show more…
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1. A Type I error is committed when __________. the null hypothesis is true and it is not rejected the null hypothesis is true and it is rejected the null hypothesis is false and it is not rejected the null hypothesis is false and it is rejected any incorrect rejection is made 2. A researcher is testing a hypothesis of a single mean. The critical z value for α = .05 and a two tailed test is ±1.96. The observed z value from sample data is minus 1.85. The decision made by the researcher based on this information is to _____ the null hypothesis. reject fail to reject redefine change the alternate hypothesis into restate 3. If α is the probability of committing a Type I error and β is the probability of committing a Type II error in a hypothesis test, the power of the test is given by __________.
Evelyn C.
Some random individual that you probably don't know comes up with a hypothesis that math professors tell much funnier jokes in class than English professors. This hilarious individual runs a hypothesis test by surveying 100 students and throwing out 47 outliers who clearly had no idea what they were talking about. By the time the hypothesis test is over, the individual finds a p-value of 0.0029. Based solely on the p-value, what can we conclude at an alpha of 0.05? We fail to reject the null, so the hypothesis is significant. We reject the null, so the hypothesis is statistically significant. We fail to reject the null, so the hypothesis is incorrect. We reject the null, so the hypothesis is correct.
Qudsiya A.
If a hypothesis test has a Type I error probability (α) of 0.01, it means that: - if the null hypothesis is false, you reject it 1% of the time. - if the null hypothesis is false, you don't reject it 99% of the time. - if the null hypothesis is true, you don't reject it 99% of the time. - if the null hypothesis is true, you reject it 1% of the time.
Adi S.
Recommended Textbooks
Elementary Statistics a Step by Step Approach
The Practice of Statistics for AP
Introductory Statistics
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