Week 3 Concept Maps

Chapter 06 Probability

Definition of Probability

Random Sampling

Probability and Proportion

Normal Distribution

Fraction or Proportion of event A

Formula: P(A) = f/N f = frequency of event A N = total number of possible Outcomes

Requirements for Random Sampling

Equal Chance

Specific Example

Probability of selecting a king from a deck = 4/52

Sampling with Replacement

All individuals have equal chance

Probability stays constant for each selection (sampling with replacement)

Restating Probability as Proportion

Use of Unit Normal Table

Probabilities can be solved by determining proportions of area in frequency Distribution

Allows finding proportions of normal distribution

Relationship with Proportions in Frequency Distribution

Proportion of Area in Distribution

Unit Normal Table

Z-scores and Probabilities

Use table to find z-scores or probabilities

X to Z formula Transform z to X or X to z

Chapter 07 Distribution of Sample Means

Definition

Central Limit Theorem

Characteristics

Z-scores and Probabilities

Set of M values for all possible random samples of size n from a population

Shape, Central Tendency, and Variability

Shape of Distribution of Sample Means

Describes parameters of the distribution of sample means

Conditions for Normal Shape

Central Tendency

Mean and Expected Value of M

Mean (M) of sample means is equal to population mean (μ)

Identifying Expected Value of M Mean of Distribution of Sample Means

Z-scores and Probabilities

Using Z-scores

Finding Probabilities

Likely and Unlikely Sample Means

Using Unit Normal Table to find probabilities

Chapter 8 - Introduction to Hypothesis Testing

Definition & Purpose

Four-Step Process

Types of Errors

Effect Size

Power of Hypothesis Testing

Using sample data to draw conclusions about a population.

Testing if a treatment has an effect on the population mean.

State the Hypothesis and select a

Null and Alt Hypothesis (H0 and H1)