Statistical Techniques & Data Interpretation Flashcards

Which measure represents the average value in a data set?

Answer: Mean

The mean, also known as the average, is calculated by summing all the values in a dataset and dividing by the number of values. It is the most commonly used measure of central tendency, representing the typical or central value of a distribution. While mode and median are also measures of central tendency, the mean specifically refers to the arithmetic average.

What does standard deviation measure in a dataset?

Answer: Spread of the data

Standard deviation is a measure of the dispersion or variability of a dataset. It quantifies the average amount by which individual data points deviate from the mean of the dataset. A low standard deviation indicates that data points tend to be close to the mean, while a high standard deviation suggests that data points are spread out over a wider range of values.

Which statistical test compares means between two groups?

Answer: T-test

A t-test is a statistical hypothesis test used to determine if there is a significant difference between the means of two groups. It is commonly employed when comparing two sample means to infer whether they come from populations with different means. ANOVA (Analysis of Variance) is used for comparing means of three or more groups, while Chi-square tests for associations between categorical variables, and regression analysis examines relationships between variables.

What type of variable is 'customer satisfaction rating on a 1-5 scale'?

Answer: Ordinal

An ordinal variable is a categorical variable where the categories have a natural order or ranking, but the differences between the categories are not necessarily equal or meaningful. A customer satisfaction rating on a 1-5 scale (e.g., 1=Very Dissatisfied, 5=Very Satisfied) clearly shows an order of satisfaction, but the difference between a 3 and a 4 might not be the same as the difference between a 4 and a 5.

Which chart is best for showing the distribution of a single continuous variable?

Answer: Histogram

A histogram is a graphical representation that displays the distribution of a single continuous variable. It uses bars to show the frequency of data points falling within specific intervals or bins. This chart is excellent for visualizing the shape, spread, and central tendency of continuous data, making it easy to identify patterns like skewness or modality.

What does a correlation coefficient close to 0 indicate?

Answer: No linear relationship

The correlation coefficient (r) measures the strength and direction of a linear relationship between two variables. A value close to 0 indicates that there is little to no linear relationship between the variables. This means that changes in one variable are not consistently associated with changes in the other in a straight-line fashion, though a non-linear relationship might still exist.

What is the purpose of using regression analysis in market research?

Answer: To evaluate associations between variables

Regression analysis is a powerful statistical technique used to model the relationship between a dependent variable and one or more independent variables. Its primary purpose in market research is to understand how changes in independent variables (e.g., advertising spend, price) affect a dependent variable (e.g., sales). This allows researchers to predict outcomes and identify key drivers of market phenomena.

Which term describes the number of times a value occurs in a dataset?

Answer: Frequency

Frequency refers to the number of times a particular value or category appears in a dataset. It is a fundamental concept in descriptive statistics, used to summarize and understand the distribution of data. Calculating frequencies helps in creating frequency tables and charts, providing a clear overview of how often each data point occurs.

Which of the following is a type of inferential statistic?

Answer: Hypothesis testing

Inferential statistics involves drawing conclusions or making predictions about a population based on a sample of data. Hypothesis testing is a core inferential statistical method used to determine if there is enough evidence in a sample to support a particular claim or hypothesis about a population. Measures like mean, median, and frequency distribution are descriptive statistics, which summarize characteristics of a sample or population without making broader inferences.