Data Analysis & Statistical Methods Flashcards

What is the mean in statistics?

Answer: The average value

In statistics, the mean is the most common measure of central tendency, representing the average value of a dataset. It is calculated by summing all the values in a set and then dividing by the total number of values. The mean provides a single value that summarizes the typical magnitude of the data.

What does standard deviation measure?

Answer: Variation or dispersion

Standard deviation is a widely used measure of the dispersion or spread of data points around the mean in a dataset. A low standard deviation indicates that data points tend to be close to the mean, while a high standard deviation suggests data points are spread out over a wider range. It helps understand the variability within a dataset.

What is a hypothesis test used for?

Answer: Test claims about populations

A hypothesis test is a statistical method used to make inferences or draw conclusions about a population based on sample data. It involves formulating a null hypothesis and an alternative hypothesis, then using statistical evidence to determine whether there is enough support to reject the null hypothesis in favor of the alternative. This allows researchers to test specific claims or theories.

What is correlation?

Answer: Strength of relationship

Correlation is a statistical measure that describes the extent to which two variables tend to move together. It quantifies the strength and direction of a linear relationship between two variables, ranging from -1 (perfect negative correlation) to +1 (perfect positive correlation). It's important to note that correlation does not imply causation.

What is the median of a data set?

Answer: The middle value

The median is a measure of central tendency that represents the middle value in a dataset when the data points are arranged in ascending or descending order. If there is an even number of data points, the median is the average of the two middle values. It is less affected by extreme outliers than the mean, making it useful for skewed distributions.

What is regression analysis used for?

Answer: Model relationships

Regression analysis is a powerful statistical technique used to model and analyze the relationship between a dependent variable and one or more independent variables. It helps to understand how the value of the dependent variable changes when any one of the independent variables is varied, while the others are held fixed. This allows for prediction and understanding of potential relationships.

What is a p-value in hypothesis testing?

Answer: Probability of observed results under null

In hypothesis testing, the p-value is the probability of obtaining observed results, or results even more extreme, assuming that the null hypothesis is true. A small p-value (typically less than 0.05) suggests that the observed data are unlikely under the null hypothesis, leading to its rejection. It helps determine the statistical significance of the evidence against the null hypothesis.

What is the purpose of a scatter plot?

Answer: Visualize variable relationships

A scatter plot is a type of data visualization that displays the relationship between two numerical variables. Each point on the plot represents a pair of values, allowing observers to visually identify patterns, trends, and correlations between the variables. It is particularly useful for detecting linear or non-linear associations and potential outliers.

What does the term 'sample size' refer to?

Answer: Number of data points collected

Sample size refers to the number of individual observations or data points included in a statistical sample. A larger sample size generally leads to more reliable and precise statistical inferences about the population from which the sample was drawn. Determining an appropriate sample size is crucial for the validity and power of a study.