Type I and Type II Errors

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Across
  1. 5. H0 The claim we seek evidence against; usually a statement of "no difference" Has the form H0: parameter = value
  2. 6. The entire group that is going to be studied.
  3. 7. An interval calculated from sample data, which has the general form estimate ± margin of error or, alternatively, statistic ± (critical value)(standard deviation of statistic).
  4. 9. The claim we hope or suspect to be true instead of the null hypothesis; we are trying to find evidence for this hypothesis Sets the direction that counts as evidence against HO
  5. 10. The alternative hypothesis is two sided if it states that the parameter is different from the null hypothesis value; when it could be either larger or smaller (two directions that counts as evidence against H0)
  6. 11. A sample that consists of the entire population is called a census.
  7. 13. When the standard deviation of a statistic is estimated from data, the result is the standard error of the statistic.
  8. 15. The specific value of a point estimator.
Down
  1. 1. The probability, computed assuming H0 is true, that the statistic would take a value as extreme as or more extreme than the one actually observed, in the direction specified by Ha (measures the strength of evidence against H0 and in favor of Ha)
  2. 2. The alternative hypothesis is one sided if it states that a parameter is larger than the null hypothesis value or if it states that the parameter is smaller than the null value (one direction that counts as evidence against H0)
  3. 3. We can compare the P-value with a fixed value that we reard as decisive
  4. 4. Should express the hopes or suspicions we have before we see the data. It is cheating to look at the data first and then frame hypotheses to fit what the data show..
  5. 8. weigh the evidence against a claim and in favor of a counter-claim
  6. 12. of error Tells how close the estimate tends to be to the unknown parameter in repeated random sampling.
  7. 13. A smaller representative group of the the population.
  8. 14. Any systematic failure of a sampling method. Overemphasizing or underemphasizing the characteristic of the Population in a Sample Group.