Statistics terms flash cards

The cards, front and back

1. 1
   Front

   Mean

   Back

   The sum of all the values divided by the number of values. It uses every value, so outliers affect it.

2. 2
   Front

   Median

   Back

   The middle value when the data is in order. For an even number of values, it is the mean of the two middle values. It is not affected much by outliers.

3. 3
   Front

   Mode

   Back

   The value that occurs most often. A data set can have one mode, more than one, or none.

4. 4
   Front

   Range

   Back

   The largest value minus the smallest value. It is a simple measure of spread but is affected by outliers.

5. 5
   Front

   Quartiles and interquartile range (IQR)

   Back

   The lower quartile (Q1) is a quarter of the way through the ordered data and the upper quartile (Q3) is three quarters of the way. IQR = Q3 − Q1, the spread of the middle half of the data.

6. 6
   Front

   Standard deviation

   Back

   A measure of how spread out the values are around the mean. A small standard deviation means the values are close to the mean.

7. 7
   Front

   Variance

   Back

   The mean of the squared distances from the mean. The standard deviation is the square root of the variance.

8. 8
   Front

   Outlier

   Back

   A value that is much bigger or smaller than the rest of the data. A common rule marks values more than 1.5 × IQR below Q1 or above Q3.

9. 9
   Front

   Population and sample

   Back

   A population is the whole group you want to know about. A sample is a smaller group chosen from it to collect data from.

10. 10
    Front

    Random sample

    Back

    A sample in which every member of the population has an equal chance of being chosen. It helps reduce bias.

11. 11
    Front

    Bias

    Back

    A systematic error that makes results unrepresentative, for example asking only people at a gym about how much exercise people do.

12. 12
    Front

    Qualitative and quantitative data

    Back

    Qualitative (categorical) data is descriptive, such as eye colour. Quantitative data is numerical, such as height.

13. 13
    Front

    Discrete and continuous data

    Back

    Discrete data can only take certain values, often counts such as the number of pets. Continuous data can take any value in a range, such as time or mass.

14. 14
    Front

    Correlation

    Back

    A relationship between two variables. Positive: as one increases, the other tends to increase. Negative: as one increases, the other tends to decrease. None: no clear pattern.

15. 15
    Front

    Does correlation prove causation?

    Back

    No. Two variables can be correlated because of chance or because a third variable affects both. An experiment is needed to show cause and effect.

16. 16
    Front

    Line of best fit

    Back

    A straight line drawn through the middle of the points on a scatter graph, used to show a trend and make estimates. Estimating outside the data range (extrapolation) is unreliable.

17. 17
    Front

    Histogram

    Back

    A chart for continuous grouped data, where the area of each bar represents the frequency. With unequal class widths, the height shows frequency density = frequency ÷ class width.

18. 18
    Front

    Box plot

    Back

    A diagram showing the minimum, lower quartile, median, upper quartile and maximum. It is useful for comparing the spread and centre of data sets.

19. 19
    Front

    Normal distribution

    Back

    A symmetrical, bell-shaped distribution where the mean, median and mode are equal. About 68% of values lie within one standard deviation of the mean, about 95% within two, and about 99.7% within three.

20. 20
    Front

    Skewed distribution

    Back

    A distribution with a longer tail on one side. In a positive (right) skew, the tail is on the right and the mean is usually greater than the median.

21. 21
    Front

    Probability

    Back

    How likely an event is, from 0 (impossible) to 1 (certain). The probability of an event not happening is 1 minus the probability that it happens.

22. 22
    Front

    Mutually exclusive and independent events

    Back

    Mutually exclusive events cannot happen at the same time, so P(A or B) = P(A) + P(B). Independent events do not affect each other, so P(A and B) = P(A) × P(B).