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# B AD 6243: Applied Univariate Statistics - PowerPoint PPT Presentation

B AD 6243: Applied Univariate Statistics. Hypothesis Testing and the T-test Professor Laku Chidambaram Price College of Business University of Oklahoma. Steps in Hypothesis Testing. Determine hypotheses (null & alternative) Select significance level (  level/p level) Choose a sample size

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### B AD 6243: Applied Univariate Statistics

Hypothesis Testing and the T-test

Professor Laku Chidambaram

University of Oklahoma

• Determine hypotheses (null & alternative)

• Select significance level ( level/p level)

• Choose a sample size

• Calculate the value of the statistic

• Obtain critical value

• Compare results

Sample (“Trial”)

Population (“Truth”)

• Maximize experimental variance

• Design, plan and conduct research so that the experimental conditions are as different as possible

• Minimize error variance

• Reduce error through controlling experimental conditions

• Reduce error by increasing reliability of measures

• Control extraneous variance

• Randomization: Groups can be considered statistically equal in all possible ways

• Selection: To eliminate the effect of an extraneous variable on a dependent variable, choose subjects so that they are as homogenous as possible (on that variable)

• Addition: To control the effect of an extraneous variable, build it into the research design, so as to measure its effect on the dependent variable

• Randomized groups

• Random sampling; random assignment

• Simple vs. factorial designs

• Concerns:

• (Pre-experimental) equality of groups

• Unequal cell sizes

• Correlated group(s)

• Use same units in different treatments

• Single vs. multi-group designs

• Concerns:

• History, maturation and sensitization

• Degrees of freedom

• T-distribution vs. standard normal distribution

• Level of significance

• Between subjects design:

• Equal sample sizes

• Equal variance

• Within subjects design

t-distributions refer to a family of distributions, which like normal distributions, are

bell-shaped, but whose shape changes with the sample size; smaller sample

sizes have flatter distributions, while larger sizes approximate normal distributions