Sample vs Population comparing mean and standard deviations

Slides:



Advertisements
Similar presentations
The Normal Distribution
Advertisements

 These 100 seniors make up one possible sample. All seniors in Howard County make up the population.  The sample mean ( ) is and the sample standard.
Sampling distributions. Example Take random sample of students. Ask “how many courses did you study for this past weekend?” Calculate a statistic, say,
Sampling distributions. Example Take random sample of 1 hour periods in an ER. Ask “how many patients arrived in that one hour period ?” Calculate statistic,
Confidence Intervals for Proportions
Standard Normal Distribution
Chapter 7: Variation in repeated samples – Sampling distributions
PROBABILITY AND SAMPLES: THE DISTRIBUTION OF SAMPLE MEANS.
The Basics  A population is the entire group on which we would like to have information.  A sample is a smaller group, selected somehow from.
Today Today: Chapter 8, start Chapter 9 Assignment: Recommended Questions: 9.1, 9.8, 9.20, 9.23, 9.25.
Chapter 11: Random Sampling and Sampling Distributions
Standard error of estimate & Confidence interval.
UNIT FOUR/CHAPTER NINE “SAMPLING DISTRIBUTIONS”. (1) “Sampling Distribution of Sample Means” > When we take repeated samples and calculate from each one,
Data Analysis: Part 3 Lesson 7.1. Data Analysis: Part 3 MM2D1. Using sample data, students will make informal inferences about population means and standard.
AP Statistics Chapter 9 Notes.
Standard Deviation!. Let’s say we randomly select 9 men and 9 women and ask their GPAs and get these data: MENWOMEN
A P STATISTICS LESSON 2 – 2 STANDARD NORMAL CALCULATIONS.
Sampling Distribution of a sample Means
Sampling Distribution of the Sample Mean. Example a Let X denote the lifetime of a battery Suppose the distribution of battery battery lifetimes has 
Chapter 6.3 The central limit theorem. Sampling distribution of sample means A sampling distribution of sample means is a distribution using the means.
Chapter 7 Sampling and Sampling Distributions ©. Simple Random Sample simple random sample Suppose that we want to select a sample of n objects from a.
Chapter 7: Introduction to Sampling Distributions Section 2: The Central Limit Theorem.
Lecture 11 Dustin Lueker. 2  The larger the sample size, the smaller the sampling variability  Increasing the sample size to 25… 10 samples of size.
Section 6-5 The Central Limit Theorem. THE CENTRAL LIMIT THEOREM Given: 1.The random variable x has a distribution (which may or may not be normal) with.
6.3 THE CENTRAL LIMIT THEOREM. DISTRIBUTION OF SAMPLE MEANS  A sampling distribution of sample means is a distribution using the means computed from.
Sampling Error SAMPLING ERROR-SINGLE MEAN The difference between a value (a statistic) computed from a sample and the corresponding value (a parameter)
§ 5.3 Normal Distributions: Finding Values. Probability and Normal Distributions If a random variable, x, is normally distributed, you can find the probability.
Review Normal Distributions –Draw a picture. –Convert to standard normal (if necessary) –Use the binomial tables to look up the value. –In the case of.
1 Sampling Distribution of Arithmetic Mean Dr. T. T. Kachwala.
Review of Statistical Terms Population Sample Parameter Statistic.
Chapter 18 - Part 2 Sampling Distribution Models for.
Sampling Distributions: Suppose I randomly select 100 seniors in Anne Arundel County and record each one’s GPA
Sec 6.3 Bluman, Chapter Review: Find the z values; the graph is symmetrical. Bluman, Chapter 63.
Central Limit Theorem Let X 1, X 2, …, X n be n independent, identically distributed random variables with mean  and standard deviation . For large n:
m/sampling_dist/index.html.
An Example of {AND, OR, Given that} Using a Normal Distribution By Henry Mesa.
MATH Section 4.4.
Chapter 9 Day 2. Warm-up  If students picked numbers completely at random from the numbers 1 to 20, the proportion of times that the number 7 would be.
Chapter 9 Sampling Distributions 9.1 Sampling Distributions.
Ch5.4 Central Limit Theorem
6.39 Day 2: The Central Limit Theorem
Differences between t-distribution and z-distribution
STANDARD ERROR OF SAMPLE
STA 291 Spring 2010 Lecture 21 Dustin Lueker.
6-3The Central Limit Theorem.
Introduction to Sampling Distributions
Chapter Six Normal Curves and Sampling Probability Distributions
An Example of {AND, OR, Given that} Using a Normal Distribution
The Normal Probability Distribution Summary
Sampling Distribution
Sampling Distribution

Year-3 The standard deviation plus or minus 3 for 99.2% for year three will cover a standard deviation from to To calculate the normal.
Central Limit Theorem.
Consider the following problem
Sampling Distribution of a Sample Proportion
Sampling Distributions
CHAPTER 15 SUMMARY Chapter Specifics
Sampling Distribution of the Mean
The estimate of the proportion (“p-hat”) based on the sample can be a variety of values, and we don’t expect to get the same value every time, but the.
Sampling Distribution of a Sample Proportion
Essential Statistics Sampling Distributions
Notes: Sample Means
Sample Means Section 9.3.
Normal Distribution.
Sampling Distributions
An Example of {AND, OR, Given that} Using a Normal Distribution
STA 291 Spring 2008 Lecture 21 Dustin Lueker.
Consider the following problem
Presentation transcript:

Sample vs Population comparing mean and standard deviations MM2D1d Compare the means and standard deviations of random samples with the corresponding population parameters, including those population parameters for normal distributions. Observe that the different sample means vary from one sample to the next. Observe that the distribution of the sample means has less variability than the population distribution.

Sample vs Population Means and Standard Deviations Let’s watch… http://www.onlinemathlearning.com/population-mean.html

Sample vs. Population Sample mean- average of the sample taken Population mean-average of everything (given, not calculated)

Sample vs. Population The sample means are higher than the population mean. The sample standard deviations are lower than the population standard deviation. Random 1 Mean-5.3 Standard Deviation-2.44 Random 2 Mean-5 Standard Deviation-2.58

Sample vs. Population For a large population, the mean is 13.7 and the standard deviation is about 8.9. Compare the mean and standard deviation of the random sample to the population parameters. 19, 8, 12, 17, 16, 25, 5, 18, 21, 7 Mean-14.8 Standard Deviation-6.23 The mean is larger and the standard deviation is smaller.

Sample vs. Population Pgae 275 (1-11)