Statistics Mastery Challenge

What are the three main measures of central tendency?

• average, range, variance

• mean, standard deviation, quartiles

• median, mode, frequency

• mean, median, mode

Define hypothesis testing in statistics.

• Hypothesis testing is a statistical method for making decisions about a population based on sample data.

• Hypothesis testing is a technique for predicting future outcomes based on past data.

• Hypothesis testing is used to summarize data without making decisions.

• Hypothesis testing is a method for collecting data from a population.

Explain the difference between correlation and regression.

• Correlation and regression are the same statistical method.

• Regression shows the relationship between three or more variables.

• Correlation indicates the degree to which two variables move in relation to each other, while regression is used to model and predict the value of one variable based on another.

• Correlation measures the strength of a single variable.

What does ANOVA stand for and when is it used?

• ANOVA stands for Analysis of Numbers and is used to calculate averages.

• ANOVA stands for Analysis of Variance and is used to compare means across multiple groups.

• ANOVA stands for Analysis of Variability and is used for regression analysis.

• ANOVA stands for Average of Normal Values and is used to assess individual performance.

Describe the purpose of a t-test.

• To determine the correlation between two variables.

• To analyze the distribution of a dataset.

• The purpose of a t-test is to compare the means of two groups to see if they are statistically different from each other.

• To measure the variance within a single group.

What is the difference between a one-tailed and a two-tailed hypothesis test?

• A one-tailed test is used for small sample sizes, whereas a two-tailed test is for large samples.

• A one-tailed test evaluates one direction of effect, whereas a two-tailed test evaluates both directions.

• A one-tailed test can only be used for positive effects, while a two-tailed test can only be used for negative effects.

• A one-tailed test evaluates both directions of effect, while a two-tailed test evaluates one direction.

How can you determine if two variables are correlated?

• Measure the mean of both variables.

• Perform a linear regression analysis.

• Calculate the correlation coefficient and visualize with a scatter plot.

• Count the number of data points.

What is the difference between descriptive and inferential statistics?

• Descriptive statistics predict future trends; inferential statistics summarize data.

• Descriptive statistics are used for qualitative data; inferential statistics are used for quantitative data.

• Descriptive statistics analyze data; inferential statistics collect data.

• Descriptive statistics summarize data; inferential statistics make predictions about a population based on a sample.

What is the purpose of a chi-square test?

• To compare the means of two groups.

• To assess the association between categorical variables.

• To analyze the variance within a single group.

• To determine the correlation between two continuous variables.

What is the main difference between parametric and non-parametric tests?

• Parametric tests assume a specific distribution for the data, while non-parametric tests do not.

• Parametric tests can only be used for large sample sizes, while non-parametric tests can be used for small samples.

• Parametric tests are always more accurate than non-parametric tests.

• Parametric tests are used for categorical data, while non-parametric tests are used for continuous data.