Concept explainers
UFOs When two people meet, they are sometimes surprised that they have similar beliefs. A survey of 1003 random adults conducted by the Scripps Survey Research Center at Ohio University found that 62 percent of men and 50 percent of women believe in intelligent life on other planets. Well, actually, they said it is either "very likely" or "somewhat likely" that intelligent life exists on other planets.
a. If a man and a woman meet, what is the
b. If a man and a woman meet, what is the probability that neither believes in intelligent life on other planets?
c. What is the probability that the man and woman agree about life on other planets?
d. If a man and a woman meet, what is the probability that they have opposite beliefs on this issue?
Want to see the full answer?
Check out a sample textbook solutionChapter 5 Solutions
Introductory Statistics (2nd Edition)
Additional Math Textbook Solutions
Math in Our World
A Problem Solving Approach To Mathematics For Elementary School Teachers (13th Edition)
APPLIED STAT.IN BUS.+ECONOMICS
Elementary Statistics: Picturing the World (7th Edition)
Probability And Statistical Inference (10th Edition)
A First Course in Probability (10th Edition)
- 55 5.5 A glass bottle manufacturing company has recorded data on the average number of defects per 10,000 bottles due to stones (small pieces of rock embedded in the bottle wall) and the number of weeks since the last furnace overhaul. The data are shown below. Defects per 10,000 Weeks 13.0 4 16.1 5 14.5 6 17.8 7 22.0 8 27.4 9 16.8 10 65.6 ☐☐ Defects per 10,000 Weeks 34.2 11 12 49.2 13 66.2 81.2 87.4 14 15 16 114.5 17 a. Fit a straight-line regression model to the data and perform the standard tests for model adequacy. b. Suggest an appropriate transformation to eliminate the problems encoun- tered in part a. Fit the transformed model and check for adequacy.arrow_forwardOne estimate of the proportion of children with autism in the United States is 1 in 100 (Source: http://www.cbsnews.com/stories/2009/10/05/health/main5363192.shtml). Suppose you are interested in the rate of autism among current school-aged children in Utah. You collect a sample of 400 children between the ages of 5 and 18 and find that three have had a previous diagnosis of an autism disorder. You plan to calculate a 95% confidence interval estimator of the proportion of school-aged children in Utah who have ever had a diagnosis of an autism disorder. Which of the following is the most likely reason you would use a Wilson estimator to calculate the confidence interval estimator? It is uncomfortable to define having been diagnosed with autism as a success. It is possible that if even the actual proportion in Utah is 1%, your sample may only have very few children who have had a previous diagnosis of an autism disorder. It is an easier way to calculate the confidence…arrow_forwardProblem 2-6. Need help on why its 1.22arrow_forward
- Scenario: As a data analyst for a retail company, you are tasked with examining the relationship between televisions screen size, and prices. Your analysis will involve both correlation and regression methods to quantify and interpret this relationship Make a Scatterplot of screen size vs. price. Explain in one sentence, does there appear to be a positive or a negative correlation between price and screen size? Paste a snapshot of the plot here. Please do not copy paste. Question 1: What is the value of correlation coefficient between screen size and price? Discuss the direction of the relationship (positive, negative, or zero relationship). Also discuss the strength of the relationship Estimate the relationship between screen size and price using a simple linear regression model and interpret the estimated coefficients. In your interpretation, tell the dollar amount by which price will change for each unit of increase in screen size. (The answer for the second part of this…arrow_forwardvery time you conduct a hypothesis test, there are four possible outcomes of your decision to reject or not reject the null hypothesis: (1) You don’t reject the null hypothesis when it is true, (2) you reject the null hypothesis when it is true, (3) you don’t reject the null hypothesis when it is false, and (4) you reject the null hypothesis when it is false. Consider the following analogy: You are an airport security screener. For every passenger who passes through your security checkpoint, you must decide whether to select the passenger for further screening based on your assessment of whether he or she is carrying a weapon. Suppose your null hypothesis is that the passenger has a weapon. As in hypothesis testing, there are four possible outcomes of your decision: (1) You select the passenger for further inspection when the passenger has a weapon, (2) you allow the passenger to board her flight when the passenger has a weapon, (3) you select the passenger for further inspection when…arrow_forwardEKS C ALEKS - Kim Johnson - Ch 6S × 4 www-awy.aleks.com alekscgi/x/sl.exe/16_u-lgNs/kr7j8FB)--BjuvZG weRMign 4tCy83MpSgONH0-ovaPm-Zym e Chrome isn't your default browser Set as default Ch 6 Sec 4 Homework Question 4 of 4 (1 point) | Question Attempt: 2 of Unlimited ✓ 2 ✓ 3 = 4 Stress at work: In a poll conducted by the General Social Survey, 81% of respondents said that their jobs were sometimes or always stressful. Two hundred workers are chosen at random. Use the TI-84 Plus calculator as needed. Round your answer to at least four decimal places. (a) Approximate the probability that 155 or fewer workers find their jobs stressful. (b) Approximate the probability that more than 145 workers find their jobs stressful. (c) Approximate the probability that the number of workers who find their jobs stressful is between 154 and 172 inclusive. Part 1 of 3 The probability that 155 or fewer workers find their jobs stressful is 0.1207 Part 2 of 3 bility that more than 145 workers find their jobs…arrow_forward
- A case-control (or retrospective) study was conducted to investigate a relationship between the colors of helmets worn by motorcycle drivers and whether they are injured or killed in a crash. Results are given in the accompanying table. Using a 0.01 significance level, test the claim that injuries are independent of helmet color. Color of Helmet Black White Yellow Red Blue Controls (not injured) 499 373 32 159 79 Cases (injured 221 108 8 66 38 or killed) Click here to view the chi-square distribution table. Chi-square distribution table Area to the Right of the Critical Value Degrees of Freedom 0.995 0.99 0.975 0.95 0.90 0.10 0.05 0.025 0.01 0.005 C. Ho: Injuries and neimet color are dependent H₁: Injuries and helmet color are independent D. Ho: Whether a crash occurs and helmet color are dependent 1 0.001 0.004 0.016 2.706 3.841 5.024 6.635 7.879 2 0.010 0.020 0.051 0.103 0.211 4.605 5.991 7.378 9.210 10.597 3 0.072 0.115 0.216 0.352 0.584 6.251 7.815 9.348 11.345 12.838 4 0.207 0.297…arrow_forwardConduct the hypothesis test and provide the test statistic and the critical value, and state the conclusion. A person drilled a hole in a die and filled it with a lead weight, then proceeded to roll it 200 times. Here are the observed frequencies for the outcomes of 1, 2, 3, 4, 5, and 6, respectively: 28, 32, 46, 39, 29, 26. Use a 0.025 significance level to test the claim that the outcomes are not equally likely. Does it appear that the loaded die behaves differently than a fair die? Click here to view the chi-square distribution table. The test statistic is (Round to three decimal places as needed.) Chi-square distribution table Area to the Right of the Critical Value Degrees of Freedom 0.995 0.99 0.975 0.95 0.90 0.10 0.05 0.025 0.01 0.005 1 0.001 0.004 0.016 2.706 3.841 5.024 6.635 2 0.010 0.020 0.051 0.103 0.211 4.605 5.991 7.378 9.210 7.879 10.597 3 0.072 0.115 0.216 0.352 0.584 6.251 7.815 9.348 11.345 12.838 4 0.207 0.297 0.484 0.711 1.064 7.779 9.488 11.143 13.277 14.860 5…arrow_forwardThe online clothing retailer e-Parel is conducting a study to estimate the average size of the orders placed by visitors to its website. The project manager desires a $60 bound on the error of estimation at 90% confidence. The population standard deviation is unknown, and a “best guess” of $175 is used as the planning value for σ. Use the Distributions tool to help you answer the questions that follow. 0123 Select a Distribution The z-value for a 90% confidence interval of the population mean is . In order to satisfy the requirement of a $60 bound on the error of estimation, a sample size no smaller than is needed.arrow_forward
- A local electronics store just received a shipment of 620 HDMI cables. The manager wants to estimate the number of defective HDMI cables in the shipment. Rather than checking every HDMI cable, the manager plans to take a simple random sample of size 62 in order to estimate the proportion of defective HDMI cables in the shipment. If the sample proportion of defective HDMI cables, p̂p̂, is greater than 0.0323 (there are more than two defective HDMI cables in the sample), the manager will file a complaint and request a new shipment. Suppose that the true proportion of defective HDMI cables in the shipment is approximately p = 0.02. What is the expected value of the sample proportion? E(Pˆ)E(P^)= Since the sample is to be drawn from a finite population, and since the sample is 5% of the population size, the finite population correction factor needed when you calculate the standard deviation of the sampling distribution. What is the standard deviation of the…arrow_forwardAn automobile battery manufacturer offers a 39/50 warranty on its batteries. The first number in the warranty code is the free-replacement period; the second number is the prorated-credit period. Under this warranty, if a battery fails within 39 months of purchase, the manufacturer replaces the battery at no charge to the consumer. If the battery fails after 39 months but within 50 months, the manufacturer provides a prorated credit toward the purchase of a new battery. The manufacturer assumes that X, the lifetime of its auto batteries, is normally distributed with a mean of 44 months and a standard deviation of 3.6 months. Use the following Distributions tool to help you answer the questions that follow. (Hint: When you adjust the parameters of a distribution, you must reposition the vertical line (or lines) for the correct areas to be displayed.) 0123 Select a Distribution If the manufacturer’s assumptions are correct, it would need to replace of its…arrow_forwardIn regards to conducting a linear contrast after a one-way ANOVA, can you explain how seemingly arbitrary weights that "emphasize or de-emphasize" certain variables in a linear combination and sum to zero are able to provide information about how certain groups differ from each other? For example, if we havethree groups A, B, and C, and we want tocompare the mean of group A with theaverage of groups B and C, the weights inthis case are 1 for group A, and -0.5 for groupsB and C, which sum to zero. But how do these numbers model the relationship of comparing one group to the average of the other two? Does it have to do with how the math is carried out, such as how the test statistic is created?arrow_forward
- College AlgebraAlgebraISBN:9781305115545Author:James Stewart, Lothar Redlin, Saleem WatsonPublisher:Cengage LearningHolt Mcdougal Larson Pre-algebra: Student Edition...AlgebraISBN:9780547587776Author:HOLT MCDOUGALPublisher:HOLT MCDOUGALAlgebra and Trigonometry (MindTap Course List)AlgebraISBN:9781305071742Author:James Stewart, Lothar Redlin, Saleem WatsonPublisher:Cengage Learning
- Algebra & Trigonometry with Analytic GeometryAlgebraISBN:9781133382119Author:SwokowskiPublisher:Cengage