Descriptive Statistics:

• What is the focus of descriptive statistics?

  Descriptive statistics focuses on summarizing and describing data.
• What is a population in statistics?

  A population is the entire group of people we’re interested in.
• What is a sample in statistics?

  A sample is a subset of our population.
• How is a sample usually represented in statistics?

  A sample is usually represented with the letter n.
• What does n represent in statistics?

  n represents our sample size.
• What types of data are there in statistics?

  There are categorical, discrete, and continuous data.
• What is categorical data?

  Categorical data has 2 or more categories with no ordering to them.
• Give an example of categorical data.

  Hair colour is an example of categorical data.
• What is discrete data?

  Discrete data has a fixed value with a logical order.
• Give an example of discrete data.

  Shoe size is an example of discrete data.
• What is continuous data?

  Continuous data can take any fractional value.
• Give an example of continuous data.

  Reaction times are an example of continuous data.
• How can categorical data be presented?

  Categorical data can be presented as its raw frequency or as a percentage frequency.
• How can discrete data be presented?

  Discrete data can be presented as a raw frequency, percentage, or cumulative frequency.
• What should you do if you have many values in your data?

  You should use frequency ranges to present the data instead.
• What are the measures of central tendency?

  1. Mode – the score that happens the most often in a dataset
  2. Median – the middle score in a dataset
  3. Mean – the sum of data points divided by the number of data points
• What is the mode in a dataset?

  The mode is the score that happens the most often in a dataset.
• For what type of data can the mode be used?

  The mode can be used for nominal data.
• What are bimodal and multimodal distributions?

  Bimodal distributions have two modes, while multimodal distributions have more than two modes.
• What is the median in a dataset?

  The median is the middle score in a dataset.
• How is the median calculated for odd value datasets?

  The median is calculated as $(n+1)/2$ for odd value datasets.
• How is the median calculated for even value datasets?

  The median is calculated as the average of the middle two values.
• What is an advantage of using the median?

  The median is insensitive to outliers.
• Why is the median often meaningful?

  The median often gives a real, meaningful data value.
• For what types of data is the median useful?

  The median is useful for ordinal data and skewed interval/ratio data.
• What is a disadvantage of using the median?

  The median ignores a lot of the data.
• What is a challenge when calculating the median?

  It can be hard to calculate the median without a computer.
• For what type of data can't the median be used?

  The median cannot be used with nominal data.
• How is the mean calculated?

  The mean is calculated as the sum of data points divided by the number of data points.
• What is an advantage of using the mean?

  The mean uses all the data.
• For what type of datasets is the mean most effective?

  The mean is most effective for normally distributed datasets.
• What is a disadvantage of using the mean?

  The mean is sensitive to outliers.
• Why might values of the mean not always be meaningful?

  Values of the mean aren’t always meaningful, such as when we cannot get a score of $6.74/10$.
• For what types of data is the mean meaningful?

  The mean is only meaningful for ratio and interval data.
• What are the measures of spread related to central tendency?

  • Mode: no measures of spread
  • Median: distance-based measures (range + interquartile range)
  • Mean: center-based measures of spread (variance + standard deviation)
• How does the interquartile range compare to the range?

  The interquartile range is similar to the range but ignores the most extreme values.
• What does the interquartile range represent?

  The interquartile range represents the range of scores within the middle 50% of the scores.
• How is the lower quartile defined?

  The lower quartile is the median of the lower half of the data.
• How is the interquartile range calculated?

  The interquartile range is calculated as the upper quartile minus the lower quartile.

  
• What are deviance and variance in statistics?

  • Deviance: Each score is subtracted from the mean, which could result in a deviance of ‘0’.
  • Variance: An average of the sum of squared errors (SS), which is the sum of squared deviances.