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STA 210: first set of notes for Exam 2

by: Cara Braido

STA 210: first set of notes for Exam 2 STA 210

Marketplace > University of Kentucky > Math > STA 210 > STA 210 first set of notes for Exam 2
Cara Braido
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About this Document

This set of notes is the CORRECT version. It covers video and in-class material from February 18th-24th
Intro to Statistical Reasoning
Jeffery Modenbach
Class Notes
Math, Statistics, University of Kentucky, UK, Beyond the Numbers




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This 2 page Class Notes was uploaded by Cara Braido on Wednesday February 24, 2016. The Class Notes belongs to STA 210 at University of Kentucky taught by Jeffery Modenbach in Spring 2016. Since its upload, it has received 78 views. For similar materials see Intro to Statistical Reasoning in Math at University of Kentucky.


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Date Created: 02/24/16
Cara Braido STA 210 Jeffery Modenbach Notes for Exam 2 th February 18 , Corresponds to pages 93 and 99 in Beyond the Numbers Video #1’s notes: Goal of sampling- to make inferences about a population from what we know about our sample data  Lists or frames from which data is taken has to be unbiased One Sentence Summary: Avoiding biased samples is just good common sense, whereas making meaningful statements from proper samples is the business of statistical science. Video #2’s notes: Sample- collection of items/subjects that you pick to examine from the population (also denoted as “n”) Statistic- # that describes the sample Population- larger collection of subjects/items that you’re interested in learning about (remember, a sample is a portion of the population) Parameter- is a value, usually unknown (and which therefore has to be estimated), used to represent a certain population characteristic (Hint: ask yourself what the study is trying to find. You won’t give a numerical value when answering a parameter question in the workbook) Simple random sample: n individuals chosen from the population in such a way that every set of n individuals had the same chance of being chosen One Sentence Summary: A probabilistic sample like an SRS is a critical step in estimating a population parameter with a simple statistic February 22 , Corresponds to page 117 in BTN Video #1’s notes: Sampling variability- variability seen in a statistic from sample to sample Sampling distribution- distribution of a statistic Confidence interval- (p hat) +/- (z* divided by 2) multiplied(square root of 1 divided by n) Margin of error- Square root of 1 divided by n p hat = sample proportion  When watching the videos and completing the book assignment, you’ll notice that it doesn’t explicitly mention the formulas you need. Check pages 263, 264. THEY WILL HELP IF YOU ARE LOST!  Lower confidence = margin of error decreases/more narrow the estimation One Sentence Summary: Simple formulas are available for the margin of error and associated confidence intervals, provided the data was collected in a simple random sample, or a similarly statistically correct fashion. What pages did we complete in lecture this week? (this includes February 24 too)th 95, 96, 101, 102, 104, 123, 124, 128


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