Unit 1, Exploring one variable data
Variables
Categorical
Quantitative
Assigns labels that place each individual into a particular group, known as category
Takes number values that are quantities; counts or measurements.
Could be represented as Bar graph or two way table
Could represented with dotplots, stemplots and histograms
Symmetric, left skewed or right skewed
Describing a distribution
Outlieres
Center
Shape
Variability
Symmetric, unimodal, bimodal, skewed
Identify whether there is a gap between the intervals, if there is, potential outlier is observed
1.5IQR rule, Q1-1.5(IQR)< X < Q3+1.5(IQR)
Mean(Symmetric), Median(Skewed graph)
Standard deviation( Symmetric), IQR(Skewed)
Making and Interpreting Boxplots
Displays quantitative data through five number summary.
- Minimum
- Maximum
- First quartile(Q1)
- Median(Q2)
- Third quartile(Q3)
When comparing two distribution, comparing words must be included.
Comparison words examples:
larger, higher, compared to, same, different, smaller, less than, etc.
Normal Distribution
Described by a symmetric, single peaked, bell shaped density curve called a normal curve
Standard Normal Distribution
Mean=0
Standard Deviation=1
Empirical Rule: 68-95-99.7
Z-Score
The number of standard deviations a value is from the mean
Standardized Score:
indicates how many standard deviations a datum is above or below the population/sample mean
Steps of making a boxplot
Find the five number summary
Identify outliers
Draw and label the axis
Draw a box Mark the median.
Draw whiskers
Be sure a Key is included. Ex: 10 | 4= 10.4
Unbiased Biased Estimator: Sample mean/proportion=population mean/proportion