'Approximately normal' diaporamas de présentation

Sampling Distribution of a Sample Proportion

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Radiology Packet 30

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5.4 The Central Limit Theorem

5.4 The Central Limit Theorem. Statistics Mrs. Spitz Fall 2008. Objectives/Assignment. How to find sampling distributions and verify their properties How to interpret the Central Limit Theorem How to apply the Central Limit Theorem to find the probability of a sample mean

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Ch 18 Simple Linear Regression

Ch 18 Simple Linear Regression. 2010.02.24. Like correlation analysis, simple linear regression is a technique to explore the relationship between two continuous random variables . What are the differences between correlation analysis and simple linear regression?

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10 November 2003

10 November 2003. 6.2 Tests of Significance 6.3 Use and Abuse of Tests 6.4 Power and Inference as a Decision. Tests of Significance. The reasoning of significance tests Stating hypotheses Test statistics p values Statistical significance Tests for a population mean

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Hypothesis Testing

Hypothesis Testing. After 2 hours of frustration trying to fill out an IRS form, you are skeptical about the IRS claim that the form takes 15 minutes on average to complete. How would you challenge the IRS claim?. Methods to Test a Claim.

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DIRECTIONAL HYPOTHESIS

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AP Exam

AP Exam . Thursday, May 17, 2018 Report at 11:30 to Vince Meyer Learning Center. Exploring Data: Describing Patterns and Departures from Patterns. We started by describing univariate (that means one variable) data graphically and numerically. Graphically:. Dotplot. Stemplot.

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Density Curves and the Normal Distribution

Density Curves and the Normal Distribution. What is a Density Curve?. Consider the following histogram Remember that the shape of the histogram depends on the width of the classes we choose for the histogram, our data might look like this!.

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9-1:Sampling Distributions ? Preparing for Inference!

9-1:Sampling Distributions ? Preparing for Inference!. Parameter : A number that describes the population (usually not known) Statistic : A number that can be computed from the sample data without making use of any unknown parameters. . Example .

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Inference on Proportions

Inference on Proportions. Assumptions:. SRS Normal distribution np > 10 & n(1-p) > 10 Population is at least 10n. Normal curve. Formula for Confidence interval:.

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Chapter 5

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Standardizing and the Standard Normal Curve

Standardizing and the Standard Normal Curve. AP Statistics. The Standardized Value (the Z score). If x is an observation from a distribution that has mean and standard deviation , the standardized value of x is. A woman 68 inches tall for example has a standardized height of

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Significance Tests and Two Proportions

Significance Tests and Two Proportions. Presentation 9.5. Working with Two Proportions. Be sure to define your proportions so you can keep track of them. For example: 1: males 2: females Use proper notation:. Properties: Sampling Distribution of p 1 - p 2.

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Section 12.2 Comparing Two Proportions

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Stat 13 Lecture 22 comparing proportions

Stat 13 Lecture 22 comparing proportions. Estimation of population proportion Confidence interval ; hypothesis testing Two independent samples One sample, competitive categories (negative covariance) One sample, non-competitive categories (usually, positive covariance). An Example.

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Things you need to know for 9.2

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STAT 135 LAB 11

STAT 135 LAB 11. Learning Objective: #72 TA: Dongmei Li. Simulations in the Law of Average Lab (Lab 10) . The number of red marbles in 38 trials: 16 16 19 17 26 13 with standard deviation =4.44597

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