Descriptive Statistics
graphical + numerical methods of summarizing data
Inferental statistics
uses descriptive statistics to estimate and make inferences about population parameters
Summation, Σ
means “add up everything that follows”
PEMDAS (order of operations)
Mean
arithmetic average of the numbers
Statistic
any characteristic or measure from a SAMPLE
Parameter
any characteristic or measure from a POPULATION
Median
data value in the middle of the ordered data
Mode
the data value that occurs most frequently in the data
Outlier
data value that is very different from the rest of the data and is far from the median
Variability
describes how the data is spread out
High variability indicates what about the data?
Data is spread out
Low variability indicates what about the data?
Data is close together
Range
difference between highest and lowest data values
Deviation
how far each data point is from the mean (𝑥 − 𝑥̅)
Variance
measure of the average squared distance from the mean
Standard deviation
Average (mean) distance from a data point to the mean; how much a typical data point differs from the mean
What is inferred by a small standard deviation?
Data is close together
What is inferred by a large standard deviation?
Data is spread out
When should you compare the range, standard deviation, or variance values of different sets of data?
ONLY when the two data sets have the same units/scales
Coefficient of variation (CVar)
standard deviation divided by mean, expressed as percentage
Find the coefficient of variation for a Crumbl cookie, when the average price is 𝑥̅ = $4.50, and standard deviation is s = $0.36. Round to two decimal places
CVar = (s/𝑥̅)x100% = 8.00%
Z-score
number of standard deviations an observation (x value) is above or below the mean
-if z-score is +1.00, the x-value is 1 standard deviation above the mean
-if z-score is -3.50, the x-value is 3.5 standard deviations below the mean
What two things does a z-score always have?
-a sign; + or -, and
-two decimal places