different types of significants testing

• one sample t test

  • compare random sample from a subpopulation against a large population

• two sample t test

  • compares differeces between two sample statistics

• ANOVA

  • compares differences across more than two groups

  • one sample significants hypothesis test for mean

• null hypothesis

  • always says there is no significant difference between the differing groups

• alternative hypothesis

  • states the observewd difference really exists in the overall population

• sterps for hypothesis testing

  • sample was selected randomly via one of the methods for attaining probability samples

  • the levels of measurmentis interval scale

  • the sampling distribution is normal in shape

• step 2

  • state hypothesis

    • null hypothesis

    • alternate hypothesis

• step 3

  • select statistic test to carry out

• step four

  • carry out statistical equations to confirm data

• make a decision and interpret the results

Two sample vs. one sample test

• two samples must be selected independantly and randomly

Anova

• mean differences between anova and t tests

  • analysis of variance: we want to know if observed differences in sample means represent

    • like a two sample test in means decompose variance to compare differences between groups toi differences within groups

• logic of anova if age plays a role in determining the support for capital punishment

  • different age groups should have a different supporting levels of capital punishment

  • particular age group should have a simular supporting levels of capital punishment