Please turn off cell phones, pagers, etc. The lecture will begin shortly.

Slides:



Advertisements
Similar presentations
Percentiles and the Normal Curve
Advertisements

Regression Inferential Methods
SUMMARIZING DATA: Measures of variation Measure of Dispersion (variation) is the measure of extent of deviation of individual value from the central value.
The Standard Normal Curve Revisited. Can you place where you are on a normal distribution at certain percentiles? 50 th percentile? Z = 0 84 th percentile?
Numerically Summarizing Data
The Normal Distribution
Normal distribution. An example from class HEIGHTS OF MOTHERS CLASS LIMITS(in.)FREQUENCY
Unit 6 Data and Statistics Review Game. Please select a Team Nemo 2.Dory 3.Bruce 4.Squirt 5.Jacques.
Measures of Dispersion or Measures of Variability
Distribution of the sample mean and the central limit theorem
NORMAL CURVE Needed for inferential statistics. Find percentile ranks without knowing all the scores in the distribution. Determine probabilities.
1.2: Describing Distributions
Multiple Choice Review
Chap 3-1 Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chapter 3 Describing Data: Numerical Statistics for Business and Economics.
12.3 – Measures of Dispersion
Chapter 11: Random Sampling and Sampling Distributions
Chapters 10 and 11: Using Regression to Predict Math 1680.
1 Normal Distributions Heibatollah Baghi, and Mastee Badii.
Understanding Research Results
Inference for Distributions
Describing distributions with numbers
9.1 – Sampling Distributions. Many investigations and research projects try to draw conclusions about how the values of some variable x are distributed.
Data Analysis 17 Data are obtained from a random sample of adult women with regard to their ages and their monthly expenditures on health products. The.
Copyright © 2011 Pearson Education, Inc. Putting Statistics to Work Discussion Paragraph 6B 1 web 26. Web Data Sets 1 world 27. Ranges in the News 28.
Please turn off cell phones, pagers, etc. The lecture will begin shortly. There will be a quiz at the end of today’s lecture.
ESTIMATION. STATISTICAL INFERENCE It is the procedure where inference about a population is made on the basis of the results obtained from a sample drawn.
Chapter 1: Research Methods
Stat 1510: Statistical Thinking and Concepts 1 Density Curves and Normal Distribution.
And the Rule THE NORMAL DISTRIBUTION. SKEWED DISTRIBUTIONS & OUTLIERS.
NOTES The Normal Distribution. In earlier courses, you have explored data in the following ways: By plotting data (histogram, stemplot, bar graph, etc.)
Descriptive Statistics Measures of Variation. Essentials: Measures of Variation (Variation – a must for statistical analysis.) Know the types of measures.
Regression. Height Weight How much would an adult female weigh if she were 5 feet tall? She could weigh varying amounts – in other words, there is a distribution.
Regression. Height Weight Suppose you took many samples of the same size from this population & calculated the LSRL for each. Using the slope from each.
Statistics and Quantitative Analysis U4320 Segment 12: Extension of Multiple Regression Analysis Prof. Sharyn O’Halloran.
Quiz 2 - Review. Descriptive Statistics Be able to interpret: -Box Plots and Histograms -Mean, Median, Standard Deviation, and Percentiles.
1 Examining Relationships in Data William P. Wattles, Ph.D. Francis Marion University.
Unit 6 Data and Statistics Review Game. Please select a Team Nemo 2.Dory 3.Bruce 4.Squirt 5.Jacques.
Please turn off cell phones, pagers, etc. The lecture will begin shortly. There will be a quiz at the end of today’s lecture. Friday’s lecture has been.
Math I: Unit 2 - Statistics
LT 4.2 Designing Experiments Thanks to James Jaszczak, American Nicaraguan School.
Please turn off cell phones, pagers, etc. The lecture will begin shortly.
Statistical analysis Outline that error bars are a graphical representation of the variability of data. The knowledge that any individual measurement.
Regression with Inference Notes: Page 231. Height Weight Suppose you took many samples of the same size from this population & calculated the LSRL for.
Box Plots. Statistical Measures Measures of Central Tendency: numbers that represent the middle of the data (mean, median, mode) Mean ( x ):Arithmetic.
© 2010 Pearson Prentice Hall. All rights reserved. CHAPTER 12 Statistics.
Multiple Choice Review Chapters 5 and 6. 1) The heights of adult women are approximately normally distributed about a mean of 65 inches, with a standard.
3 Some Key Ingredients for Inferential Statistics.
BPS - 5th Ed. Chapter 31 The Normal Distributions.
Essential Statistics Chapter 31 The Normal Distributions.
AP Statistics Wednesday, 23 September 2015 OBJECTIVE TSW (1) quiz over means, boxplots, and variability, and (2) review for Friday’s test. GET OUT –WS.
Unit 6 – confidence intervals
Outline of Today’s Discussion 1.The Distribution of Means (DOM) 2.Hypothesis Testing With The DOM 3.Estimation & Confidence Intervals 4.Confidence Intervals.
Hypothesis Testing Introduction to Statistics Chapter 8 Feb 24-26, 2009 Classes #12-13.
Chapter 131 Normal Distributions. Chapter 132 Thought Question 2 What does it mean if a person’s SAT score falls at the 20th percentile for all people.
The Normal Distribution Chapter 2 Continuous Random Variable A continuous random variable: –Represented by a function/graph. –Area under the curve represents.
The Normal Approximation for Data. History The normal curve was discovered by Abraham de Moivre around Around 1870, the Belgian mathematician Adolph.
Review Design of experiments, histograms, average and standard deviation, normal approximation, measurement error, and probability.
Regression Inference. Height Weight How much would an adult male weigh if he were 5 feet tall? He could weigh varying amounts (in other words, there is.
z-Scores, the Normal Curve, & Standard Error of the Mean
AP Statistics Empirical Rule.
Regression.
Basic Statistics Overview
Linear transformations
Chapter 12 Regression.
Regression.
Regression.
Regression.
Regression.
Regression.
CHAPTER 12 Statistics.
Presentation transcript:

Please turn off cell phones, pagers, etc. The lecture will begin shortly.

Lecture 35 Today’s lecture will review key material from the first half of the semester. We will discuss questions similar to those you are likely to find on the final exam.

1.The average causal effect of dieting on body weight in a population is… A.the difference in average body weight between those in the population who diet and those in the population who do not diet B.the average weight in the population if everyone dieted, minus the average weight if no one dieted C.the average drop in weight that you would observe if all non-dieters went on a diet D.the average increase in weight that you would observe if all dieters stopped dieting

2.An education researcher wants to investigate differences in math achievement between students in local public and Catholic schools in Philadelphia. She obtains a list of all 5 th graders enrolled in public schools and all 5 th graders enrolled in Catholic schools. Then she randomly samples 100 students from each list and gives them a math achievement test. This is an example of: A.systematic sampling B.cluster sampling C.stratified sampling D.a matched-pair design

3. Which of the following is not a key advantage of a randomized experiment over an observational study? A.Randomized experiments allow us to obtain unbiased estimates of average causal effects. B.Randomized experiments eliminate confounding. C.Randomized experiments eliminate interactions. D.In a randomized experiment, there are no systematic differences between the groups receiving the different treatments

4. A pharmaceutical company runs a clinical trial to test a new drug for treating schizophrenia. They randomly assign patients to receive either the drug or a placebo. On average, patients who receive the drug showed greater improvement than those who received the placebo. Moreover, the drug seemed to be more effective in helping patients whose initial symptoms were very severe than patients who were not as severe. The latter is an example of A.confounding B.interaction C.Hawthorne effect D.correlation, as opposed to causation

5.It is often said that “correlation does not imply causation.” Remembering this is crucial when we try to interpret the results of A.surveys of all kinds B.randomized experiments of all kinds C.observational studies of all kinds D.studies with small sample size

6.Which of the following is not a common rationale for using a randomized block design instead of a completely randomized design? A.Using randomized blocks ensures that the treatment groups will be balanced with respect to important characteristics. B.Randomized block designs tend to give more precise estimates of the treatment effect. C.Randomized block designs reduce the possibility that, just by chance, the subjects in one treatment group will be very different from the subjects in another treatment group. D.Randomized block designs eliminate confounding.

7.Suppose the heights of 4 year-old boys are approximately normally distributed in the population with a mean of 40.4 inches and a SD of 1.5 inches. A doctor says that your 4 year-old brother is “at the 75 th percentile of the height distribution for his age.” About how tall is he? A (.67 × 1.5) inches B.40.4 – (.75 × 1.5) inches C.(75 – 40.4) / 1.5 inches D.(67 – 40.4) / 1.5 inches

8.In a sample of adult women, a linear regression of Y = weight (pounds) on X = height (inches) yields the following equation: A.If a woman is 62 inches tall, her predicted weight is – (3.45 × 62) pounds B.Height and weight are positively correlated. C.The intercept is not a meaningful prediction. D.Weight is the explanatory variable and height is the response. Y = – X Which of the following statements is false?

9.Examine the boxplot below. Which of the following statements is wrong? A.The lower quartile is a little less than 90. B.The interquartile range is about 15. C.The largest observation is about 130. D.The distribution looks symmetric.

10. If systolic blood pressure is normally distributed with mean 125 and standard deviation 25, about what percentage of the population has systolic pressure above 150? A.5% B.9% C.16% D.32%

11. A Stat 100 instructor gives a very easy quiz. Students’ scores (out of 10 points) are shown below. (The zero scores are for students who didn’t come to class.) A.The median, mode and maximum are equal. B.The interquartile range is zero. C.The standard deviation is zero. D.The mean is less than the median Which of the following statements is false?

12. You are hired by the IRS to analyze data from a sample of federal income tax returns for What correlation would you expect to find between X = income and Y = taxes paid? A.positive but not 1.0 B.near zero C.less than zero D.close to -1.0