Data interpretation

Descriptive statistics

when researchers organize and describe the data that is being collected

inferential statistics

when researchers make predictions about their data and independent variables. they help researchers determine if the data from a sample can be applied to a population

null hypothesis

there is no effect of difference between the variables. it serves as a baseline for testing

alternative hypothesis

there is an effect or difference between the variables

effect size

strength of relationship between the variables. tells us how meaningful effect is in real world terms

statistical significance

tells us whether the difference is likely real or due to chance

frequency distribution table

allows researchers to see how often sets of data occur

frequency polygon

visual representation of frequency distribution table, with all points connected

histogram

bar graph that displays frequencies through vertical columns

pie chart

data is divided into sections of a circle, each representing a proportion of the whole

central tendency

mean, median, mode

mean

average of data set. take the sum of all values and divide by the number of values

regression toward a mean

as you add more data points, it becomes closer to the mean since outliers are less impactful

mode

value that occurs most often

median

value that is exact middle of the data set

range

subtract highest and lowest data point

standard deviation

researchers can indicate average distance from the mean for a data set

normal distribution

classic bell shaped curve

positive skew

values are low and clustered to the left of the mean

negative skew

values are high and clustered to the right of the mean

bimodal distribution

a distribution has 2 modes. represented by 2 peaks

z-score

a numerical representation that describes how many standard deviations a particular value is from the average or mean. positive=higher than mean, negative=lower than mean

percentile rank

the percentage of scores at or below a particular score

positive correlation

as one variable increases, so does the other

negative correlation

as one variable increases, the other variable decreases