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by: kyle dunham

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2

# stats review Math 14500-02

kyle dunham
IC
GPA 3.5

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review for exam
COURSE
Statistics for health, life, and social sciences
PROF.
James E Conklin
TYPE
Study Guide
PAGES
2
WORDS
CONCEPTS
stats math
KARMA
50 ?

## Popular in Math

This 2 page Study Guide was uploaded by kyle dunham on Friday March 4, 2016. The Study Guide belongs to Math 14500-02 at Ithaca College taught by James E Conklin in Spring 2016. Since its upload, it has received 23 views. For similar materials see Statistics for health, life, and social sciences in Math at Ithaca College.

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Date Created: 03/04/16
Statistics Review Quantitative vs. Categorical -Quantitative: deals with numbers only and data. Ex: the height of children in the class. -Categorical: puts items in a category. One group vs another. Numerical measures of data: The mean: Average Median: The middle number Range: Max-Min Standard Deviation: How spread out the numbers are Variance: measures how far a set of numbers are spread out. Quartiles: Q1: Separates the bottom 25% of data from the top 75%. Q3: Seperates the bottom 75% from the top 25%. Q2: Median Outliers: numbers that are more than 1.5 IQR (interquartile range) away from Q1 and Q3. Extreme outliers are 3 times bigger or smaller (3 IQR). IQR: Interquartile range is Q3-Q1 Correlation: How closely related the two variables are to each other. We use graphs to see this. z-scores: formula= x-mean/standard deviation. Z-score tells us how many standard deviations we are from the mean. Characteristics of distributions: look over these terms: Symmetric (mean=median) Left skewed (mean<median) Right skewed (mean>median) Bell-Shaped (Normal distribution) Sampling with/without replacement: Bootstrap sample: sample with replacement from the original Introduction to Regression: -Least square lines (also called best fit lines)=goal is to approximate the data. Formual: y hat (calculated value for y)=mx+b -residuals: The vertical distance from a data point to the best fit line. Formual= y-y hat predictions: A guess based on the data 95% Rule for bell-shaped curves: If a distribution is bell shaped then about 95% of data value land within 2 Standard Deviations of the mean Experimentation Vs Observation: Observation should conclude causation and there could be confounding variables. Experimentation: Researcher decides often randomly who gets which treatment; there usually aren’t any volunteers. Association Vs Causation: Matched pair Vs Independent samples Population parameters vs. sample statistics: Parameters are for population and statistics are just for one single individual

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