Exam_Review_1
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Exam_Review_1

Course: STA 2014, Fall 2010

School: University of Florida

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Exam 1 Review Questions. 1. Administrators at a large university want to know the average debt incurred by their graduates. Surveys were mailed to 210 graduates asking them to report their total student loan debt. Identify the population and sample in the study. 2. Identify the following variables as quantitative or qualitative. If quantitative say if it's discrete or continuous. a) the colors of book covers on a...

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1 Exam Review Questions. 1. Administrators at a large university want to know the average debt incurred by their graduates. Surveys were mailed to 210 graduates asking them to report their total student loan debt. Identify the population and sample in the study. 2. Identify the following variables as quantitative or qualitative. If quantitative say if it's discrete or continuous. a) the colors of book covers on a bookshelf b) the weight of a player on the wrestling team c) the age of the oldest employee in the data processing department d) the numbers on the shirts of a boys football team 3. Determine whether the following are observational studies or designed experiments. a) The personnel director at a large company would like to determine whether the company cafeteria is widely used by employees. She calls each employee and asks them whether they usually bring their own lunch, eat at the company cafeteria, or go out for lunch b)A researcher obtained a random sample of 100 smokers and a random sample of 100 nonsmokers. After interviewing all 200 participants in the study, the researcher compared the rate of depression among the smokers with the rate of depression among nonsmokers. c) A scientist was studying the eects of a new fertilizer on crop yield. She randomly assigned half of the plots on a farm to group one and the remaining 1 plots to group two. On the plots in group one, the new fertilizer was used for a year. On the plots in group two, the old fertilizer was used. At the end of the year the average crop yield for the plots in group one was compared with the average crop yield for the plots in group two. 4. Determine which sampling technique has been used. (simple random, cluster, systematic, stratied, convenience) a) At a local technical school, ve auto repair classes are randomly selected and all of the students from each class are interviewed. b) A lobbyist for the oil industry assigns a number to each senator and then uses a computer to randomly generate ten numbers. The lobbyist contacts the senators corresponding to these numbers. c)A sample consists of every 35th worker from a group of 4000 workers. d)To avoid working late, the plant foreman inspects the rst 60 microwaves produced that day. 5. Determine the type of bias a) A local hardware store wants to know if its customers are satised with the customer service they receive. The store posts an interviewer at the front of the store to ask the rst 50 shoppers who leave the store, How satised, on a scale of 1 to 10, were you with this stores customer service? b) Before opening a new dealership, an auto manufacturer wants to gather information about car ownership and driving habits of the local residents. The marketing manager of the company randomly selects 1000 households from all households in the area and mails a questionnaire to them. Of the 1000 surveys mailed, she receives 70 back. 6. Listed below are the STA2014 scores from the rst exam taken in the semester in a thirty class. 2 27 71 69 87 55 89 84 85 89 85 56 82 67 75 21 77 65 82 65 78 78 student 45 32 96 46 66 83 80 31 55 a) Construct a relative frequency table with a class width of 10 starting at 10. b) Construct a relative frequency histogram c) Describe the shape of the distribution 7. The number of yards that a football player rushed in randomly selected 13 games of his NFL career are listed below. 3 49 32 33 39 22 42 9 9 39 52 58 70 a) Find the mean , mode and median for this data set and write them using the proper notation. b) Describe the shape of the distribution. 8. The following data represents a random sample of 15 complaints registered with the customer service department of a store. Other Defective Product Mesy Store Messy Store Other Other Other Other Messy Store Waiting Time Other Other Waiting time Messy Store Defective Product Determine the best measure of central tendency to use, and write its value. 9. Health care issues are receiving much attention in both academic and political arenas. A sociologist recently conducted a survey of citizens over 60 years of age whose net worth is too high to qualify for government health care but who have no private health insurance. The ages of 25 uninsured senior citizens were as follows: 68 73 66 76 86 74 61 89 65 90 69 92 76 62 81 63 68 81 70 73 60 87 75 64 82 Suppose the mean and standard deviation are 74.0 and 9.7, respectively. If we assume that the distribution of ages is bell shaped, what percentage of the 3 respondents will be between 64.3 and 93.4 years old? 10. At a tennis tournament a statistician keeps track of every serve. The statistician reported that the mean serve speed of a particular player was 99 miles per hour (mph) and the standard deviation of the serve speeds was 15 mph. If nothing is known about the shape of the distribution. What is the minimum percentage of serves with speeds between 61.5 and136.5 mph? 11. Test scores for a statistics class had a mean of 79 with a standard deviation of 4.5. Test scores for a calculus class had a mean of 69 with a standard deviation of 3.7. Suppose a student gets a 60 on the statistics test and a 87 on the calculus test. On which test did the student perform better relative to the other students in each class? 12. The test scores of 30 students are listed below. 31 41 45 48 52 55 56 56 63 65 67 67 69 70 70 74 75 78 79 79 80 81 83 85 85 87 90 92 95 99 a) Compute the ve number summary. b) Examine if any outliers are present. c) Draw a boxplot. d) Indicate the shape of the distribution. e) Calculate the range 13. Indicate if the following statements are true or false: a) ( ) For a left skewed distribution, the median is smaller than the mean. b) ( )The square root of the standard deviation is known as variance. c)( )Discrete quantitative data is represented by a bar graph. d) ( )One can observe the shape of a distribution using a stem and leaf plot. e) () The First Quartile represents the tenth percentile. 4

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University of Florida - STA - 2014
Finding the Mean (Expectation), Variance, and Standard Deviationof a Discrete Probability DistributionUsing the STAT Menu of the TI-83/TI-84 Graphing Calculator1. To find the mean, , of the distribution of a discrete random variable X:a) Choose STAT,
University of Florida - STA - 2014
Hypothesis Tests Some ExamplesExample 1: Directional hypothesis test for a population mean.The U. S. Food and Drug Administration recommends that individuals consume 1000 mg ofcalcium daily. The International Dairy Foods Association (IDFA) sponsors and
University of Florida - STA - 2014
STEPS IN STATISTICAL HYPOTHESIS TESTINGStep 1: State the null hypothesis, H0, and the alternative hypothesis, Ha. The alternativehypothesis represents what the researcher is trying to prove. The null hypothesis represents thenegation of what the resear
University of Florida - STA - 2014
Statistics 2014Among the skills that you will be learning in this course are techniques for graphing data. Below is atype of graph that we will be looking at later in the course. You might find that this graph providesyou with some useful information.
University of Florida - STA - 2014
Chapter 2 Organizing and Summarizing DataDefinition: When data are in their original form, as collected, they are called raw data.We want to be able to visualize the characteristics of a data set; hence we construct graphicalrepresentations of the data
University of Florida - STA - 2014
Chapter 3 Numerically Summarizing DataAfter we have become somewhat familiar with the data through representing it graphically andobserving the characteristics of the distribution, we want to describe the characteristics with numericalvalues called des
University of Florida - STA - 2014
Ch 4 Describing the Relation between Two VariablesDefinition: When the values of two variables are measured for each member of a population orsample, the resulting data is called bivariate.When both variables are quantitative, we may represent the data
University of Florida - STA - 2014
Chapter 5 ProbabilityDefn: A random experiment is one for which the outcome cannot be predicted with certainty.Defn: The set of all possible outcomes of a random experiment is called the sample space of theexperiment.Defn: An event is a subset of the
University of Florida - STA - 2014
Chapter 5 ProbabilityDefn: A random experiment is one for which the outcome cannot be predicted with certainty.Defn: The set of all possible outcomes of a random experiment is called the sample space of theexperiment.Defn: An event is a subset of the
University of Florida - STA - 2014
Chapter 6 The Binomial Probability DistributionDefn: A random variable is a variable whose values are determined by chance. We will denote arandom variable by a capital letter, such as X, and denote particular values of the variable by thecorresponding
University of Florida - STA - 2014
Chapter 7 The Normal Probability DistributionThe normal distribution is a special type of bell-shaped curve.Defn: A random variable X is said to be normally distributed or to have a normal distribution if itsdistribution has the shape of a normal curve
University of Florida - STA - 2014
Chapter 8 Sampling DistributionsDefn: Sampling error is the error resulting from using a sample to infer a populationcharacteristic.Example: We want to estimate the mean amount of Pepsi-Cola in 12-oz. cans coming off anassembly line by choosing a rand
University of Florida - STA - 2014
Chapter 9 Estimating the Value of a ParameterUsing Confidence IntervalsThere are two branches of statistical inference, 1) estimation of parameters and 2) testing hypothesesabout the values of parameters. We will consider estimation first.Defn: A poin
University of Florida - STA - 2014
Chapter 10 Testing Claims Regarding a ParameterThe other branch of statistical inference is concerned with testinghypotheses about the value of parameters.Defn: A hypothesis is a statement about the value of a populationparameter.Defn: In a hypothesi
University of Florida - STA - 2014
Normal Approximation to the Binomial DistributionUsing the Central Limit TheoremAssume that I select a random sample of size n from a population, where n is large. For eachmember of the sample, I want the answer to a yes-or-no question. For sample memb
University of Florida - STA - 2014
1Understanding Probability LawsLet a random experiment have sample space S. Any assignment of probabilities to events must satisfy three basic laws ofprobability, called Kolmogorovs Axioms:1) For any event A, P(A) 0.2) P(S) = 1.3) If A and B are two
University of Florida - STA - 2014
Statistics 2014, Spring 2010Final Exam Review TopicsChapter 1 Data CollectionStatistics, Population, Sample, Parameter, Statistic, Variable, DataBranches of statistics: Descriptive, InferentialTypes of data: 1) Attribute, or qualitative 2) Numerical,
University of Florida - STA - 2014
Review 3 STA 20141. Mahalo Burgers, Inc, claims that the mean gross revenue of Mahalo Burgers stores is $300000 per year witha standard deviation of $72000.a) If a random sample of 38 stores in the franchise is selected, describe the sampling distribut
University of Florida - STA - 2014
Sampling Distributions and the Central Limit TheoremWhenever we select a random sample from a population, collect data from the members of thesample, and summarize the data values in the form of a statistic, that statistic is a random variable(dependin
University of Florida - STA - 2014
Statistics 2014, Spring 2010Exam 2 Review TopicsChapter 5 ProbabilityRandom experiment.Sample spaceEvents: Simple event; Compound event.Assigning probabilities to events:Classical approach: equally likely outcomesRelative frequency (empirical) app
University of Florida - STA - 2014
STA2014 Review For Exam 21.The data below are the nal exam scores of 10 randomly selected history students and the number of hours theyslept the night before the exam. Suppose we want to predict the score of the exam using the hours slept the night befo
University of Florida - STA - 2014
University of Florida - STA - 2014
University of Florida - STA - 2014
University of Florida - STA - 2014
University of Florida - STA - 2014
University of Florida - STA - 2014
University of Florida - STA - 2014
University of Florida - STA - 2014
University of Florida - STA - 2014
University of Florida - STA - 2014
University of Florida - STA - 2014
University of Florida - STA - 2014
University of Florida - STA - 2014
STEPS IN STATISTICAL HYPOTHESIS TESTINGStep 1: State the null hypothesis, H0, and the alternative hypothesis, Ha. The alternative hypothesisrepresents what the researcher is trying to prove. The null hypothesis represents the negation of what theresear
University of Florida - STA - 2014
STA 2014 Elementary Statistics for Health andSocial Science Majors Fall 2010Section: 82136Instructor: Pablo CrespoOce: Building 51 Room 3127Phone: ?E-mail: pablo.crespo@unf.eduURL:http:/www.unf.edu/~pablo.crespo/Oce Hours: MW 1:30-2:30 PM and TR 1
University of Florida - STA - 2014
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Ohio State - STA - 528
Ohio State - STA - 528
Ohio State - STA - 528
Statistics 528: Homework 2Due Friday, January 231. IPS Section 1.2 exercises 1.41, 1.45, 1.50, 1.58, 1.722. IPS Section 1.3 exercises 1.78, 1.86, 1.88, 1.98, 1.112, 1.140Problem 1.140 is a bit more open-ended than other problems in the text.The idea
Ohio State - STA - 528
Ohio State - STA - 528
Ohio State - STA - 528
Ohio State - STA - 528
Statistics 528: Homework 4Due Wednesday, February 41. IPS Section 2.3, exercises 2.40, 2.46, 2.522. IPS Section 2.4, exercises 2.58, 2.64NOTE: See lecture notes 10 for information on performing least squaresregression using MINITAB.3. IPS Section 2.
Ohio State - STA - 528
Ohio State - STA - 528
Statistics 528: Homework 5Due Wednesday, Feb. 111. IPS Section 3.1, exercise 3.82. IPS Section 3.2, exercises 3.10, 3.14, 3.16, 3.32See MINITAB Handout 3 for instructions on using MINITAB for problems 3.14and 3.32.3. IPS Section 3,3, exercises 3.38,
Ohio State - STA - 528
Ohio State - STA - 528
Ohio State - STA - 528
Ohio State - STA - 528
Statistics 528: Homework 7Due Monday, March 11. IPS Section 5.1, exercises 5.2, 5.6, 5.8, 5.14Use Minitab for the calculation of binomial probabilities (see lecture notes 19).2. IPS Section 5.2, exercises 5.28, 5.33, 5.38, 5.44
Ohio State - STA - 528
Ohio State - STA - 528
Ohio State - STA - 528
Ohio State - STA - 528
Ohio State - STA - 528
Ohio State - STA - 528
Ohio State - STA - 528
Ohio State - STA - 528
Statistics 528 - Lecture 3Section 1.1/1.2Graphical and Numerical Summaries of DataShape of a Distribution Modes Symmetric vs. Skewed OutliersMeasures of the Center mean medianMeasures of Spread IQR standard deviationChoosing Summaries of Dist
Ohio State - STA - 528
Statistics 528 - Lecture 3Section 1.1/1.2Graphical and Numerical Summaries of DataModesShape of a DistributionQuestion: Does the distribution have one or several major peaks? Modes Symmetric vs. Skewed OutliersA distribution with one major peak i
Ohio State - STA - 528
Statistics 528 - Lecture 4Section 1.3Density CurvesMathematical model for the distribution of a variableAlternative to graphical and numerical summariesIdealized description - histogram of the data is not exactly the same asthe curveCompact represe
Ohio State - STA - 528
Statistics 528 - Lecture 4Section 1.3Relative Frequency of Scores Less Than or Equal to 6.0Density CurvesMathematical model for the distribution of a variableAlternative to graphical and numerical summariesIdealized description - histogram of the da
Ohio State - STA - 528