 2.2.1: Relationship between attendance at class and final exam. You want t...
 2.2.2: Create a categorical variable from a quantitative variable. Conside...
 2.2.3: Replace names by ounces. In the Mocha Frappuccino example, the vari...
 2.2.4: Sleep and stress or stress and sleep? Consider the scenario describ...
 2.2.5: High click counts on Twitter. A study was done to identify variable...
 2.2.6: Explanatory or response? For each of the following scenarios, class...
 2.2.7: Buy and sell prices of used textbooks. Think about a study designed...
 2.2.8: Protein and carbohydrates. Think about a study designed to examine ...
 2.2.9: Can you examine the relationship? For each of the following scenari...
 2.2.10: Examine the spreadsheet. Examine the spreadsheet that gives the lau...
 2.2.11: Use the data set. Using the data set from the previous exercise, cr...
 2.2.12: Make a scatterplot. (a) Make a scatterplot similar to Figure 2.1 fo...
 2.2.13: Change the units. (a) Create a spreadsheet for the laundry detergen...
 2.2.14: Make a scatterplot. In our Mocha Frappuccino example, the 12ounce ...
 2.2.15: Are the debts in 2009 and 2010 approximately the same? Use the meth...
 2.2.16: The relationship between debt in 2005 and debt in 2010. Make a plot...
 2.2.17: Is a linear relationship the best description? Look carefully at th...
 2.2.18: Bone strength. Osteoporosis is a condition where bones become weak....
 2.2.19: Bone strength for baseball players. Refer to the previous exercise....
 2.2.20: Compare the baseball players with the controls. Refer to the previo...
 2.2.21: College students by state. In Example 1.19 (page 21) we examined th...
 2.2.22: Decay of a radioactive element. Barium137m is a radioactive form o...
 2.2.23: Use a log for the radioactive decay. Refer to the previous exercise...
 2.2.24: Make some sketches. For each of the following situations, make a sc...
 2.2.25: Whats wrong? Explain what is wrong with each of the following: (a) ...
 2.2.26: Whats in the beer? The website beer100.com advertises itself as You...
 2.2.27: More beer. Refer to the previous exercise. (a) Make a scatterplot o...
 2.2.28: Internet use and babies. The World Bank collects data on many varia...
 2.2.29: Try a log. Refer to the previous exercise. (a) Make a scatterplot o...
 2.2.30: Make another plot. Refer to Exercise 2.28. (a) Make a new data set ...
 2.2.31: Explanatory and response variables. In each of the following situat...
 2.2.32: Parents income and student loans. How well does the income of a col...
 2.2.33: Reading ability and IQ. A study of reading ability in schoolchildre...
 2.2.34: purpose of the study cited in Exercise 2.33 was to ask whether scho...
 2.2.35: Body mass and metabolic rate. Metabolic rate, the rate at which the...
 2.2.36: Team value in the NFL. Management theory says that the value of a b...
 2.2.37: Records for men and women in the 10K. Table 2.1 shows the progress ...
 2.2.38: Laundry detergents. Example 2.8 describes data on the rating and pr...
 2.2.39: Change the units. Refer to the previous exercise. Express the price...
 2.2.40: Correlations and scatterplots. Explain why you should always look a...
 2.2.41: Interpret some correlations. For each of the following correlations...
 2.2.42: When should you not use a correlation? Describe two situations wher...
 2.2.43: Bone strength. Exercise 2.18 (page 98) gives the bone strengths of ...
 2.2.44: Bone strength for baseball players. Refer to the previous exercise....
 2.2.45: College students by state. In Exercise 2.21 (page 99) you used a sc...
 2.2.46: Decay of a radioactive element. Data for an experiment on the decay...
 2.2.47: Decay in the log scale. Refer to the previous exercise and to Exerc...
 2.2.48: Thinking about correlation. Figure 2.9 (page 97) is a scatterplot o...
 2.2.49: Brand names and generic products. (a) If a store always prices its ...
 2.2.50: Strong association but no correlation. Here is a data set that illu...
 2.2.51: Alcohol and carbohydrates in beer. Figure 2.10 (page 100) gives a s...
 2.2.52: Alcohol and carbohydrates in beer revisited. Refer to the previous ...
 2.2.53: Internet use and babies. Figure 2.11 (page 100) is a scatterplot of...
 2.2.54: NFL teams. In Exercise 2.36 (page 102) you used graphical summaries...
 2.2.55: Use the applet. You are going to use the Correlation and Regression...
 2.2.56: Use the applet. Go to the Correlation and Regression applet. Click ...
 2.2.57: An interesting set of data. Make a scatterplot of the following dat...
 2.2.58: High correlation does not mean that the values are the same. Invest...
 2.2.59: Student ratings of teachers. A college newspaper interviews a psych...
 2.2.60: Whats wrong? Each of the following statements contains a blunder. E...
 2.2.61: IQ and GPA. Table 1.3 (page 29) reports data on 78 seventhgrade st...
 2.2.62: Plot the line. Make a sketch of the data in Example 2.18 and plot t...
 2.2.63: Predict the fat gain. Use the regression equation in Example 2.19 t...
 2.2.64: Would you use the regression equation to predict? Consider the foll...
 2.2.65: What fraction of the variation is explained? Consider the following...
 2.2.66: Bone strength. Exercise 2.18 (page 98) gives the bone strengths of ...
 2.2.67: Bone strength for baseball players. Refer to the previous exercise....
 2.2.68: Predict the bone strength. Refer to Exercise 2.66. A young male who...
 2.2.69: Predict the bone strength for a baseball player. Refer to Exercise ...
 2.2.70: Compare the predictions. Refer to the two previous exercises. You h...
 2.2.71: Leastsquares regression for radioactive decay. Refer to Exercise 2...
 2.2.72: Leastsquares regression for the log counts. Refer to Exercise 2.23...
 2.2.73: College students by state. Refer to Exercise 2.21 (page 99) and Fig...
 2.2.74: College students by state without the four largest states. Refer to...
 2.2.75: Make predictions and compare. Refer to the two previous exercises. ...
 2.2.76: College students by state. Refer to Exercise 2.21 (page 99), where ...
 2.2.77: College students by state without the four largest states. Refer to...
 2.2.78: Data generated by software. The following 20 observations on Y and ...
 2.2.79: Alcohol and carbohydrates in beer. Figure 2.10 (page 100) gives a s...
 2.2.80: Alcohol and carbohydrates in beer revisited. Refer to the previous ...
 2.2.81: Always plot your data! Table 2.2 presents four sets of data prepare...
 2.2.82: Add an outlier. Refer to Exercise 2.78. Add an additional observati...
 2.2.83: Add a different outlier. Refer to Exercise 2.78 and the previous ex...
 2.2.84: Progress in math scores. Every few years, the National Assessment o...
 2.2.85: The regression equation. The equation of a leastsquares regression ...
 2.2.86: Metabolic rate and lean body mass. Compute the mean and the standar...
 2.2.87: IQ and selfconcept. Table 1.3 (page 29) reports data on 78 seventh...
 2.2.88: Use an applet for progress in math scores. Go to the TwoVariable S...
 2.2.89: A property of the leastsquares regression line. Use the equation f...
 2.2.90: Class attendance and grades. A study of class attendance and grades...
 2.2.91: Revenue and value of NFL teams. In Exercises 2.36 and 2.54, you use...
 2.2.92: Find the predicted value and the residual. Lets say that we have an...
 2.2.93: Find the sum of the residuals. Here are the 16 residuals for the NE...
 2.2.94: Bone strength. Exercise 2.18 (page 98) gives the bone strengths of ...
 2.2.95: Bone strength for baseball players. Refer to the previous exercise....
 2.2.96: Leastsquares regression for radioactive decay. Refer to Exercise 2...
 2.2.97: Leastsquares regression for the log counts. Refer to Exercise 2.23...
 2.2.98: College students by state. Refer to Exercise 2.21 (page 99), where ...
 2.2.99: College students by state using logs. Refer to the previous exercis...
 2.2.100: Compare numbers of college students over time. The data file COLYEA...
 2.2.101: College students over time using logs. Refer to the previous exerci...
 2.2.102: Make some scatterplots. For each of the following scenarios, make a...
 2.2.103: Whats wrong? Each of the following statements contains an error. De...
 2.2.104: Whats wrong? Each of the following statements contains an error. De...
 2.2.105: Internet use and babies. Exercise 2.28 (page 100) explores the rela...
 2.2.106: A lurking variable. The effect of a lurking variable can be surpris...
 2.2.107: Hows your selfesteem? People who do well tend to feel good about t...
 2.2.108: Are big hospitals bad for you? A study shows that there is a positi...
 2.2.109: Does herbal tea help nursinghome residents? A group of college stu...
 2.2.110: Price and ounces. In Example 2.2 (page 82) and Exercise 2.3 (page 8...
 2.2.111: Use the applet. It isnt easy to guess the position of the leastsqu...
 2.2.112: Use the applet. Go to the Correlation and Regression applet. Click ...
 2.2.113: Education and income. There is a strong positive correlation betwee...
 2.2.114: Dangers of not looking at a plot. Table 2.2 (page 125) presents fou...
 2.2.115: Read the table. How many children aged 11 to 13 met the requirement...
 2.2.116: Read the margins of the table. How many children aged 5 to 10 were ...
 2.2.117: Explain the computation. Explain how the entry for the children age...
 2.2.118: Explain the marginal distribution. Explain how the marginal distrib...
 2.2.119: Find the percent. Show that the percent of children 11 to 13 years ...
 2.2.120: A conditional distribution. Perform the calculations to show that t...
 2.2.121: Does drivers ed help? A study is planned to look at the effect of d...
 2.2.122: Music and video games. You are planning a study of undergraduates i...
 2.2.123: Eight is enough. A healthy body needs good food, and healthy teeth ...
 2.2.124: Survival and class on the Titanic. In Exercise 1.27 (page 25) you c...
 2.2.125: Number of credits and grade point average. A study of undergraduate...
 2.2.126: Punxsutawney Phil. At Gobblers Knob in Punxsutawney, Pennsylvania, ...
 2.2.127: Exercise and adequate sleep. A survey of 656 boys and girls who wer...
 2.2.128: Adequate sleep and exercise. Refer to the previous exercise. (a) Fi...
 2.2.129: Which hospital is safer? Insurance companies and consumers are inte...
 2.2.130: Patients in poor or good condition. Refer to the previous exercise....
 2.2.131: Complete the table. Here are the row and column totals for a twowa...
 2.2.132: Construct a table with no association. Construct a 3 3 table of cou...
 2.2.133: Examples of association. Give three examples of association: one du...
 2.2.134: The five criteria for establishing causation. Consider the five cri...
 2.2.135: Iron and anemia. A lack of adequate iron in the diet is associated ...
 2.2.136: Stress and lack of sleep in college students. Studies of college st...
 2.2.137: Online courses. Many colleges offer online versions of some courses...
 2.2.138: Marriage and income. Data show that men who are married, and also d...
 2.2.139: Exercise and selfconfidence. A college fitness center offers an ex...
 2.2.140: Computer chip manufacturing and miscarriages. A study showed that w...
 2.2.141: Hospital size and length of stay. A study shows that there is a pos...
 2.2.142: Watching TV and low grades. Children who watch many hours of televi...
 2.2.143: Artificial sweeteners. People who use artificial sweeteners in plac...
 2.2.144: Exercise and mortality. A sign in a fitness center says, Mortality ...
 2.2.145: Effect of a math skills refresher initiative. Students enrolling in...
 2.2.146: Survival and gender on the Titanic. In Exercise 2.124 (page 149) yo...
 2.2.147: Survival, class, and gender on the Titanic. Refer to the previous e...
 2.2.148: Fan loyalty. A study of fan loyalty compared Chicago Cubs fans with...
 2.2.149: Marketing in Canada. Many consumer items are marketed to particular...
 2.2.150: Nunavut. Refer to the previous exercise and Figures 2.32 and 2.33. ...
 2.2.151: Compare the provinces with the territories. Refer to the previous e...
 2.2.152: Dwelling permits and sales for 21 European countries. The Organisat...
 2.2.153: Dwelling permits and production. Refer to the previous exercise. (a...
 2.2.154: Sales and production. Refer to the previous two exercises. (a) Make...
 2.2.155: Remote deposit capture. The Federal Reserve has called remote depos...
 2.2.156: How does RDC vary across the country? The survey described in the p...
 2.2.157: Fields of study for college students. The following table gives the...
 2.2.158: Fields of study by country for college students. In the previous ex...
 2.2.159: Graduation rates. One of the factors used to evaluate undergraduate...
 2.2.160: Popularity of a first name. The Social Security Administration main...
 2.2.161: You select the name. Refer to the previous exercise. Choose a first...
 2.2.162: For this exercise we consider a hypothetical employee who starts wo...
 2.2.163: Look at the residuals. Refer to the previous exercise. Figure 2.35 ...
 2.2.164: Try logs. Refer to the previous two exercises. Figure 2.36 is a sca...
 2.2.165: Make some predictions. The individual whose salary we have been stu...
 2.2.166: Faculty salaries. Here are the salaries for a sample of professors ...
 2.2.167: Find the line and examine the residuals. Refer to the previous exer...
 2.2.168: Bigger raises for those earning less. Refer to the previous two exe...
 2.2.169: Firefighters and fire damage. Someone says, There is a strong posit...
 2.2.170: Eating fruits and vegetables and smoking. The Centers for Disease P...
 2.2.171: Education and eating fruits and vegetables. Refer to the previous e...
 2.2.172: Predicting text pages. The editor of a statistics text would like t...
 2.2.173: Plywood strength. How strong is a building material such as plywood...
 2.2.174: Distribution of the residuals. Some statistical methods require tha...
 2.2.175: An example of Simpsons paradox. Mountain View University has profes...
 2.2.176: Construct an example with four schools. Refer to the previous exerc...
 2.2.177: Class size and class level. A university classifies its classes as ...
 2.2.178: Health conditions and risk behaviors. The data file BRFSS gives sev...
Solutions for Chapter 2: Looking at DataRelationships
Full solutions for Introduction to the Practice of Statistics: w/CrunchIt/EESEE Access Card  8th Edition
ISBN: 9781464158933
Solutions for Chapter 2: Looking at DataRelationships
Get Full SolutionsThis expansive textbook survival guide covers the following chapters and their solutions. Since 178 problems in chapter 2: Looking at DataRelationships have been answered, more than 35913 students have viewed full stepbystep solutions from this chapter. Introduction to the Practice of Statistics: w/CrunchIt/EESEE Access Card was written by and is associated to the ISBN: 9781464158933. This textbook survival guide was created for the textbook: Introduction to the Practice of Statistics: w/CrunchIt/EESEE Access Card, edition: 8. Chapter 2: Looking at DataRelationships includes 178 full stepbystep solutions.

Assignable cause
The portion of the variability in a set of observations that can be traced to speciic causes, such as operators, materials, or equipment. Also called a special cause.

Categorical data
Data consisting of counts or observations that can be classiied into categories. The categories may be descriptive.

Chisquare test
Any test of signiicance based on the chisquare distribution. The most common chisquare tests are (1) testing hypotheses about the variance or standard deviation of a normal distribution and (2) testing goodness of it of a theoretical distribution to sample data

Components of variance
The individual components of the total variance that are attributable to speciic sources. This usually refers to the individual variance components arising from a random or mixed model analysis of variance.

Conditional probability
The probability of an event given that the random experiment produces an outcome in another event.

Continuous distribution
A probability distribution for a continuous random variable.

Continuous random variable.
A random variable with an interval (either inite or ininite) of real numbers for its range.

Control chart
A graphical display used to monitor a process. It usually consists of a horizontal center line corresponding to the incontrol value of the parameter that is being monitored and lower and upper control limits. The control limits are determined by statistical criteria and are not arbitrary, nor are they related to speciication limits. If sample points fall within the control limits, the process is said to be incontrol, or free from assignable causes. Points beyond the control limits indicate an outofcontrol process; that is, assignable causes are likely present. This signals the need to ind and remove the assignable causes.

Correlation coeficient
A dimensionless measure of the linear association between two variables, usually lying in the interval from ?1 to +1, with zero indicating the absence of correlation (but not necessarily the independence of the two variables).

Crossed factors
Another name for factors that are arranged in a factorial experiment.

Decision interval
A parameter in a tabular CUSUM algorithm that is determined from a tradeoff between false alarms and the detection of assignable causes.

Degrees of freedom.
The number of independent comparisons that can be made among the elements of a sample. The term is analogous to the number of degrees of freedom for an object in a dynamic system, which is the number of independent coordinates required to determine the motion of the object.

Designed experiment
An experiment in which the tests are planned in advance and the plans usually incorporate statistical models. See Experiment

Error mean square
The error sum of squares divided by its number of degrees of freedom.

Estimate (or point estimate)
The numerical value of a point estimator.

Exponential random variable
A series of tests in which changes are made to the system under study

Fixed factor (or fixed effect).
In analysis of variance, a factor or effect is considered ixed if all the levels of interest for that factor are included in the experiment. Conclusions are then valid about this set of levels only, although when the factor is quantitative, it is customary to it a model to the data for interpolating between these levels.

Fraction defective
In statistical quality control, that portion of a number of units or the output of a process that is defective.

Fraction defective control chart
See P chart

Goodness of fit
In general, the agreement of a set of observed values and a set of theoretical values that depend on some hypothesis. The term is often used in itting a theoretical distribution to a set of observations.