Join StudySoup for FREE

Get Full Access to
UO - MATH 243 - Study Guide

Description

Reviews

• Chapter 1: Picturing Distributions with Graphs • Chapter 2: Describing Distributions with Numbers • Chapter 3: The Normal Distributions

• Chapter 8: Producing Data: Sampling • Chapter 9: Producing Data: Experiments • Chapter 12: Introducing Probability

• Chapter 15: Sampling Distributions

• Chapter 16: Confidence Intervals: The Basics • Chapter 17: Tests of Significance: The Basics • Chapter 18: Inference in Practice

• Excel Functions

• Histogram

• Box Plots

• Stemplots

• Bar Graphs If you want to learn more check out What new media object can be transcoded into different formats?

• Pie Charts

• Calculate the median and mean (average) of a set of observations

◦Mean (average): add up all numbers and divide by how many numbers in a data set

Don't forget about the age old question of What is a measure of thunderstorm potential based on vertical temperature lapse rate, moisture content of the lower atmosphere, and vertical extent of the moist layer?

If you want to learn more check out In basic building elements, what is typically used for foundation walls?

• 5-number summary

◦First quartile: average of the first half of the numbers (not including the median) ◦Third quartile: average of the last half of the numbers (not including the median)

• Normal distributions N(μ,σ), standard Normal distribution N(0,1), Normal distribution of a sample N(μ,σ/√n)

Normal distribution N(0,1)

• shape of a distribution: skewed right, skewed left, symmetric Don't forget about the age old question of What is the density of the asthenosphere?

◦skewed right:

◦skewed left:

◦symmetric: bell-shaped curve

• What is a density curve?

• Calculate proportion of observations from a Normal distribution using table A

• z-scores

◦z=(x-μ)/σ

◦(x = μ + zσ)

• 68-95-99.7 rule

◦approximations

• Terminology about sampling (population, sample, simple random sample (SRS), bias, etc.) ◦population: an entire group of individuals We also discuss several other topics like What are the economic, social, and political characteristics of developing countries?

◦sample: part of the population from which we collect information

◦simple random sample (SRS): SRS of size n consists of n individuals from the population chosen in such a way that every set of n individuals has an equal chance to be the sample actually selected

◦bias: when an outcome is favored

◦sample design: describes exactly how to select a sample from a population ◦convenience sample: taking members from a population that are easiest to reach

◦voluntary sample: consists of people who choose themselves by responding to broad appeal Don't forget about the age old question of Define tort.

• Terminology about experiments and observational studies (treatments, subjects, factors, matched pairs, control, randomization, etc.)

◦treatments: any specific experimental condition applied to the subjects

◦subjects: individuals in an experiment

◦factors: explanatory variables

◦matched pairs: A matched pairs design compares two treatments. Choose pairs of subjects that are closely matched as possible. Use chance to decide which subject in a pair gets the first treatment. Sometimes each "pair" in a matched pairs design consists of just one subject who gets both treatments. The order of the treatments is randomized. ◦control: something that other things can be compared to

◦randomization: used to decrease bias

◦statistically significant: when an observed effect so large that it would rarely occur by chance

• Sample spaces, discrete and continuous probability models

◦sample space: the set of all possible outcomes in a random phenomenon ◦discrete probability models: a probability model with a finite sample space (each outcome is given a probability and the sum of those probabilities is 1)

◦continuous probability models: assigns probabilities as areas under a density curve. The sample space is a range of values

‣ Example: Let X be a randomly chosen number between 0 and 1

• S= {all numbers between 0 and 1}

• S={X|0<X<1}

• calculate probabilities: in a discrete probability distribution AND in a continuous probability distribution like heights of men

• Population distributions and sampling distributions (and their relationship)

• Central Limit Theorem

• give confidence intervals for different confidence μ (with known σ) (x ± z √n ) and understand the margin of error and how to change its size.

• understand how to compute critical values (z∗) for different confidence levels.

• Understand Null and Alternative Hypotheses

◦Null Hypothesis: the claim tested by a statistical test

◦Alternative Hypothesis: the claim that we're trying to find evidence for

• calculate P-values and perform z tests for a population mean

• describe P-values relative to significance levels α (alpha)

SAMPLE PROBLEM: