Descriptive And Inferential Statistics Quiz

Descriptive statistics are a branch of statistics that provide simple summaries about the sample and the measures. They summarize a given data set, which can either be a representation of the entire population or a sample. Inferential statistics, on the other hand, make inferences about populations using data drawn from the population. Instead of just describing the data, inferential statistics use the data to make generalizations, estimations, predictions, or decisions.

A confidence interval gives an estimated range of values which is likely to include an unknown population parameter. It provides an interval estimate of a population parameter rather than a point estimate. The confidence interval quantifies the level of uncertainty around the estimate of the parameter.

Standard deviation is a measure of the amount of variation or dispersion of a set of values. A low standard deviation indicates that the values tend to be close to the mean of the set, while a high standard deviation indicates that the values are spread out over a wider range.

A Type II error occurs when the null hypothesis is false, but erroneously fails to be rejected. It is failing to assert what is present, a miss. While a Type I error is a false positive, a Type II error is a false negative.

The p-value is a statistical concept that provides a measure of the evidence against the null hypothesis. It is used in hypothesis testing to help you support or reject the null hypothesis. The p-value represents the probability that the results of your test occurred at random. If the p-value is small, one rejects the null hypothesis.

The null hypothesis is a general statement or default position that there is no relationship between two measured phenomena, or no association among groups. It is the hypothesis that the researcher seeks to disprove, reject or nullify.

A Type I error occurs when the null hypothesis is true, but is rejected. It is asserting something that is absent, a false hit. A Type I error is often considered to be more serious, and therefore more important to avoid, than a Type II error.

A Z-score is a numerical measurement that describes a value’s relationship to the mean of a group of values. It is a measure of how many standard deviations an element is from the mean. It can be placed on a normal distribution curve.

Correlation is a statistical measure that expresses the extent to which two variables are linearly related. It ranges from -1 to 1, with -1 indicating a perfect negative correlation, +1 indicating a perfect positive correlation, and 0 indicating no correlation at all. It gives us a measure of the strength and direction of the relationship between two variables.

Histograms and pie charts are common methods of displaying data in descriptive statistics. A histogram is a graphical representation that organizes a group of data points into a specified range, showing the data’s distribution. Pie charts, on the other hand, are circular charts divided into sectors or ‘pie slices’, usually illustrating numerical proportion.