units together Flashcards
What is the difference between parameters and statistics?
Parameters (𝜃) are conclusions about a population, while statistics (መ𝜃) are conclusions about a sample. Statistics are used as estimators of parameters.
What is the purpose of inferential statistics?
Inferential statistics is used to make conclusions about a population based on data from a sample, using probability theory.
What are the three types of hypotheses discussed in the text?
The three types of hypotheses are conceptual, operative, and statistical.
What is a conceptual hypothesis?
A conceptual hypothesis is a direct statement that is easy to understand.
What is an operational hypothesis?
An operational hypothesis is a hypothesis that is quantifiable, measurable, and analyzable and informs how the concepts will be measured.
What is a statistical hypothesis?
A statistical hypothesis is formulated in terms of statistics or parameters and is precise and specific.
What is a null hypothesis (H0)?
A null hypothesis (H0) is always stated in terms of equality, suggesting no effect, difference, or association. It is the opposite of the alternative hypothesis.
What is an alternative hypothesis (H1)?
An alternative hypothesis (H1) is the opposite of the null hypothesis, suggesting an effect, difference, or association. It is based on the research hypothesis.
What is a directional hypothesis?
A directional hypothesis predicts a particular direction of difference between populations.
What is a non-directional hypothesis?
A non-directional hypothesis does not predict a particular direction of difference.
What is the relationship between null and alternative hypotheses?
Null and alternative hypotheses are complementary and exclusive; accepting one entails rejecting the other.
What does a one-tailed hypothesis test imply?
A one-tailed test is used with a directional hypothesis and tests for a difference in a specific direction.
What does a two-tailed hypothesis test imply?
A two-tailed test is used with a non-directional hypothesis and tests for a difference in either direction.
What is a p-value?
A p-value is the probability of finding a particular statistic by chance, given that the null hypothesis (H0) is true.
What does a low p-value indicate?
A low p-value reduces the probability of the null hypothesis (H0) being true and indicates statistical significance.
What is the typical significance level (α) used in hypothesis testing?
A typical significance level (α) is 0.05, meaning a probability of chance lower than 5% is considered significant.
What is a Type I error?
A Type I error occurs when the null hypothesis (H0) is true but is rejected. It is a false positive.
What is a Type II error?
A Type II error occurs when the null hypothesis (H0) is false but is accepted. It is a false negative.
What is a confidence interval?
A confidence interval is an estimation of a range of values within which the true population parameter is likely to be found, with a high and known probability.
What are parametric tests?
Parametric tests make assumptions about the parameters of the population distribution, often assuming the population data are normally distributed.
What are non-parametric tests?
Non-parametric tests are ‘distribution-free’ and can be used for non-normal variables.
When is a standard distribution used for hypothesis testing on means?
A standard (normal) distribution is used when the population variance or standard deviation is known.
When is a Student’s t-distribution used?
A Student’s t-distribution is used when the population variance or standard deviation is unknown, or when two means are compared.
What is ANOVA used for?
ANOVA (Analysis of Variance) is used to compare more than two means. It uses the Snedecor’s F statistic.
What is the Chi-Square test used for?
The Chi-Square test is used to test associations between two categorical variables.
What is the Pearson correlation test used for?
The Pearson correlation test is used to test the linear relationship between two quantitative variables.
What is the general linear model?
The general linear model is a set of parametric analyses that aim to predict a variable based on one or more other variables, assuming a linear relationship.
What is linear regression used for?
Linear regression is used to predict changes in a dependent variable (Y) from changes in an independent variable (X).
What is the coefficient of determination (R²)?
The coefficient of determination (R²) indicates the proportion of the variability in the dependent variable (Y) that can be explained by the independent variable(s) (X). It is calculated as the square of the correlation coefficient.
What is the purpose of hypothesis testing in the regression model?
Hypothesis testing in the regression model is used to determine if the model provides a good degree of prediction of the result variable and to determine if the independent variable is a significant predictor of the dependent variable.
