Common distributions include z score, t score, and chi-squared. The type of distribution is dictated by features of the data. Determine which statistic and distribution we should use.The values 0.05 and 0.01 are common values used for alpha, but any positive number between 0 and 0.50 could be used for a significance level. The smaller the alpha, the most costly the experiment. If we are very concerned about this possibility occurring, then our value for alpha should be small. A Type I error occurs when we reject a null hypothesis that is actually true. A significance level is typically denoted by the Greek letter alpha. Choose which significance level that we want.The statement from the first step that makes the statement that a parameter equals a particular value is called the null hypothesis, denoted H 0.The statement containing inequality is called the alternative hypothesis and is denoted H 1 or H a. This could simply be a "not equals" sign, but could also be an "is less than" sign ( ). Identify which of the two symbolic statements does not have equality in it. These statements will use symbols such as inequalities and equals signs. Express both of the statements from the first step in mathematical symbols.Also, form a statement for the case that the hypothesis is false. Begin by stating the claim or hypothesis that is being tested.
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