Statistics

A/B testing is a way to compare two versions of something to find out which version performs better

• optimized product performance • improve customer experience.

• describe or summarize the main features of a dataset. • Descriptive stats are very useful because they let you quickly understand a large amount of data. • mean, median, etc

summarize your data using a single number

• measures of central tendency • measures of dispersion

Measures of central tendency like the mean, let you describe the center of your database

• measures of dispersion like standard deviation, let you describe the spread of your dataset or the amount of variation in your data points. • standard deviation

• allow data professionals to make inferences about a dataset based on a sample of the data. • use samples to make inferences about populations.

• Descriptive • Inferential

• Population includes every possible element that you are interested in measuring. • parameter: is a characteristic of a population • ex. height of the entire population of giraffes is a parameter.

• sample is a subset of a population. • A statistic is a characteristic of a sample, • ex. The average height of a random sample of 100 giraffes is a statistic.

• parameter: is a characteristic of a population (height) • statistic is a characteristic of a sample (avg height)

Mean, Median, Mode

• median is the middle value in a dataset. • This means half the values in the dataset are larger than the median and half are smaller.B

• most frequently occurring value in the dataset. • A dataset can have • no mode, • one mode or • more than one mode.

Mean: no outliers Median: have outliers Mode: categorical

sensitive to outliers

because it clearly shows you which category occurs most frequently.

• Range • standard deviation

• range is the difference between the largest and smallest value in a dataset. • quick understanding of the overall spread of your dataset.

• A Measure of Spread • Variance is a way to measure how spread out a set of numbers is. It tells you how much the numbers “vary” from the average (or mean). • average of the squared difference of each data point from the mean. • standard deviation squared

• Standard deviation measures how spread out your values are from the mean of your dataset. • The larger the standard deviation, the more spread out your values are from the mean.

help you determine the position of a value in relation to other values in a dataset.

• percentiles • quartiles • interquartile range