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Data Analysis Flashcards

5 cards from real MDTP practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.

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  1. Which of the following best describes the mean of a data set?

    Answer: The sum of all values divided by the number of values

    The mean, often referred to as the average, is a measure of central tendency calculated by summing all the values in a data set and then dividing by the total number of values. It represents the arithmetic average of the data. This calculation provides a single value that summarizes the center of the data.

  2. What is the median of the data set 3,7,9,15,18?

    Answer: 9

    The median is the middle value in a data set when the values are arranged in numerical order. For the ordered data set 3, 7, 9, 15, 18, the value 9 is precisely in the middle, with an equal number of values above and below it. If there were an even number of values, the median would be the average of the two middle numbers.

  3. Which measure of central tendency is most affected by extreme values?

    Answer: Mean

    The mean is the measure of central tendency most significantly affected by extreme values, also known as outliers. Because the mean is calculated by summing all values, a single unusually high or low value can disproportionately pull the average towards it. In contrast, the median is more resistant to the influence of outliers.

  4. In a data set, the range is defined as:

    Answer: The difference between the highest and lowest values

    The range is a simple measure of data dispersion that indicates the spread of a data set. It is calculated by subtracting the lowest value from the highest value in the set. This provides a quick and easy way to understand the total span of the data.

  5. A scatter plot is most useful for determining:

    Answer: The relationship between two variables

    A scatter plot is a graphical tool specifically designed to display the relationship between two quantitative variables. By plotting individual data points, it allows for visual identification of patterns, trends, and the strength and direction of correlation between the variables. It helps determine if there's a positive, negative, or no relationship.

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