Statistika Quiz

What is hypothesis testing?

• Hypothesis testing is a technique used to analyze qualitative data.

• Hypothesis testing is a statistical method used to make inferences or conclusions about a population based on sample data.

• Hypothesis testing is a method used to collect data from a population.

• Hypothesis testing is a process of determining the sample size for a study.

What are the steps involved in hypothesis testing?

• Formulating hypotheses, choosing significance level, collecting and analyzing data, calculating test statistic, determining critical value or p-value, making decision and interpreting results.

• Formulating hypotheses, choosing sample size, collecting and analyzing data, calculating test statistic, determining critical value or p-value, making decision and interpreting results.

• Formulating theories, selecting sample size, collecting and analyzing data, calculating test statistic, determining critical value or p-value, making decision and interpreting results.

• Formulating hypotheses, choosing confidence level, collecting and analyzing data, calculating test statistic, determining critical value or p-value, making decision and interpreting results.

What is a null hypothesis?

• A null hypothesis is a statement that assumes there is only one variable in a study.

• A null hypothesis is a statement that assumes there is a significant relationship between two variables in a study.

• A null hypothesis is a statement that assumes there is a negative relationship between two variables in a study.

• A null hypothesis is a statement that assumes there is no significant relationship between two variables in a study.

What is an alternative hypothesis?

• A statement that supports or confirms the null hypothesis in a statistical hypothesis test.

• A statement that is unrelated to the null hypothesis in a statistical hypothesis test.

• A statement that is only used in qualitative research and not in statistical hypothesis testing.

• A statement that contradicts or negates the null hypothesis in a statistical hypothesis test.

What is the significance level in hypothesis testing?

• Level at which we determine the sample size.

• Level at which we fail to reject the null hypothesis.

• Threshold at which we reject the null hypothesis

• Level at which we accept the null hypothesis.

What is a p-value?

• A p-value is a measure of the variability in a statistical analysis.

• A p-value is a measure of the effect size in a statistical analysis.

• A p-value is a measure of the sample size in a statistical analysis.

• A p-value is a statistical measure that helps determine the significance of a hypothesis test.

What is regression analysis?

• Regression analysis is a statistical method used to model the relationship between a dependent variable and one or more independent variables.

• Regression analysis is a method used to analyze categorical data.

• Regression analysis is a technique used to predict future outcomes based on historical data.

• Regression analysis is a method used to analyze the relationship between two dependent variables.

What are the types of regression analysis?

• exponential regression

• stepwise regression

• lasso regression

• linear regression, multiple regression, polynomial regression, logistic regression, and ridge regression

What is the difference between simple linear regression and multiple linear regression?

• Simple linear regression involves one independent variable, while multiple linear regression involves more than one independent variable.

• Simple linear regression is a more accurate model than multiple linear regression.

• Simple linear regression is used for categorical data, while multiple linear regression is used for numerical data.

• Simple linear regression involves multiple independent variables, while multiple linear regression involves only one independent variable.

What is the coefficient of determination (R-squared) in regression analysis?

• The coefficient of determination is the slope of the regression line.

• Proportion of the variance in the dependent variable explained by the independent variables.

• The coefficient of determination measures the strength of the relationship between the independent and dependent variables.

• The coefficient of determination is used to determine the significance of the regression model.