Definitions and Terms: Know the major definitions and terms for example

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Population

Sample

Descriptive Statistic

Inferential Statistics

Parameter vs Statistics

Variable

a. Categorical

Statistic

estimates Parameter

b. Quantitative estimates , sample mean

, population

i. Discrete mean s, sample standard estimates

, population ii. Continuous deviation standard deviation

Random Variable estimates P, population

ˆ

p , sample

Sampling Distributions proportion proportion

Parameter (Defines a population)

Statistic (calculated from sample to estimate a parameter)

Central Limit Theorem

Law of Large Numbers

Confidence Level

(1- )*100

Type I error (rejecting the null hypothesis when in fact it is true)

Type II error (not rejecting the null hypothesis when in fact the null is not true)

What is true

What you did

Do not

Reject H0

Reject H0

H0 true

No Error

Type I error Ha True

Type II

Error

No Error

15. Level of Significance (The probability of making a Type I error)

16. Interpretation of a confidence interval

17. P-value

a. The probability of making a type I error based on your sample

b. The probability, computed supposing the H0 to be true, that the test statistic will take a value at least as extreme as that actually observed.

18. Interpretation of a test of significance (hypothesis test)

Types of Problems

1. Reading and interpreting graphs (make sure you read the labels so you know units and whether the graph is frequency (counts) or relative frequency (percents, ratios, probabilities). 2. Calculating Measures of Center

a. Mean

b. Median

3. Calculating Measures of Spread

a. Range

b. You will not have to calculate the standard deviation, but you must understand what the standard deviation is – the average distance each data value is from the mean. c. Interquartile Range (Q3 – Q1)

i. 1st quartile ii. 2nd