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### 21 Cards in this Set

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 What is Research Design a logical pan to help increase our knowledge in a particular area. 2 purposes of Research Design Provide answers to researach questions Control variance, insuring tha tthe resutls obtained are as closely related to what is being studied. Maximincon the confidence level that can be placed in accurately assessing the degree of couse and effect you have in a result of the research endeavor Maximize Maximize the variance of the variables of the substantive research hypothosis: you want the experimental conditions to be as differenct as possible Control To control extraneous variables: these are indipendent bariables that are not necessarily related to your study. ex: sex race Minimize Minimize the arror variance: this is the fluctuation that may occur in your results due to random event Variable any phenomena or characeristic that is free to vary w/ at least 2 conditions or levels: ex: gender w/ both males and females is a variable, males along would be a constant. Constant is restricted to a single state ex: gender is a constant if females only are used in a studay, not both sexes. Demographic variables are used to define your sample gender, age race relegion marital status Independent variable are the presumed cause Dependent variables the presumed effect and vary as related to the independent variable Usually the treatment being tested is the independent variable hypothesis proposition that is stated in a testable form. It predicts a particular relationship between tow or more variables. There can be more than 1 hypothesis. "if" and "then" Null Hypothesis the hypothesis of "no difference". generally used in statistical analysis to be disproved. The resarch or the working hypothesis is the hypothesis you will be testing. The research hypothesis is what you want to support. Random Sample a planned process that utilizes probability theory to ensure that the sample will represent the population. Each subject in the population has an equal chance of being selected. Generalizability the true goal of research. you take what you know about a small group or sample of a population and apply it to explain the general population. inferential statistics robust powerful statistics help the researcher make "inferences" or assumptions about a population. These have strong rules and strong guidelines. Parametric types of tests Analysis of Variance aka ANOVA aka F test: compares means of more than 2 groups. t Test: compares means of 2 groups Pearson's Rho or Pearson's R: compares the association or correlation between 2 groups. Descriptive Statistics: NONPARAMETRIC tests - no strong rules or guidlelines, less confidence Includes: chi-square test: most common type, copares the observered value w/ the expected Spearman Rho: a non-parametric correlational. Correlation Means there is an association between 2 variables Positive Association as on goes up the other goes up and as one goes down the other goes down. Negative or inverse association as one goes up the other goes down and as one goes down the other goes up.