A new factory worker is put to work assembling gadgets. He is fairly slow at first, but over a period of daysgets much faster. His employer constructs the following table to evaluate is progress over the first 20 days heis on the job. Give an upper estimate for the number of gadgets the worker assembled the second 10 days onthe job. (Use 2 intervals)Number of days10520150on the jobNumber ofgadgets2023815assembled perday24

Answered: Image /qna-images/answer/39496873-ea92-477f-b1a1-6a60f80b811e.jpg

Answered: A new factory worker is put to work…

Big Ideas Math A Bridge To Success Algebra 1: Student Edition 2015

1st Edition

ISBN:9781680331141

Author:HOUGHTON MIFFLIN HARCOURT

Publisher:HOUGHTON MIFFLIN HARCOURT

Chapter11: Data Analysis And Displays

Section: Chapter Questions

Problem 12CR

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Joaquin gets paid every Friday. FI is paychecks for the past 8 Fridays were $315, $236.25, $236.25, $236.25, $315, $315, $236.25, $393.75. Find the (a) mean, (b) median, and (c) mode.
A group of researchers are studying high school students risk behvior. Among other dempgrapic charcterisitics, the students were asked how many days per week they were phisically active. In a random sample of 100 students, the mean responce was 3.75. From past studies the reseachers assumed a standard devation of 2.5 days for individual students A) what conditions need to be checked to buld a confrence interval here? B) Assuming the previous question's condition are satisfied, how is the distrubution of sample means distributed? c) Build a 95% confedence interval for the average of all students days of activity per week.
An industrial supplier has shipped a truckload of teflon lubricant cartridges to an aerospace customer. The customer has been assured that the mean weight of these cartridges is in excess of the 11 ounces printed on each cartridge. To check this claim, a sample of n=23 cartridges are randomly selected from the shipment and carefully weighed. Summary statistics for the sample are: x= 11.14 ounces, s= .23 ounce. To determine whether the supplier's claim is true, consider the test, H0: μ= 11 vs Ha: μ=> 11, where μ is the true mean weight of the cartridges. Calculate the value of the test statistic. Select one: A. 0.609 B. 2.919 C. 1.400 D. 14.000
An industrial supplier has shipped a truckload of teflon lubricant cartridges to an aerospace customer. The customer has been assured that the mean weight of these cartridges is in excess of the 10 ounces printed on each cartridge. To check this claim, a sample of n=10 cartridges are randomly selected from the shipment and carefully weighed. Summary statistics for the sample are: x=10.11 ounces, s=.30 ounce To determine whether the supplier's claim is true, consider the test, H 0: μ = 10 vs. H a: μ > 10 vs. where μ is the true mean weight of the cartridges. Find the rejection region for the test using a=.01 t > 3.25, where t depends on 9 df |z| > 2.58 z > 2.33 t > 2.821, where t depends on 9 df
Rochelle was curious about the gender ratio in mechanical engineering versus chemical engineering in American universities. She obtained separate random samples of 30 students from each field of study. She found that 5 of the mechanical engineering students in her sample were female, and 10 of the chemical engineering students in her sample were female. She plans to use these results to make a two-sample zzz interval to estimate the difference between the proportion of females in each field of study. Which conditions for constructing this type of interval did Rochelle's samples meet? I. Both samples were randomly selected from their populations. II. The counts of successes and failures are sufficiently large in each sample. III. Individual observations in each sample can be considered independent, and the samples themselves are independent.
The control department of a light bulb manufacturer randomly picks 4400 light bulbs from the production lot every week. The records show that, when there is no malfunction, the defect rate in the manufacturing process (due to imperfections in the material used) is 1%. When 1.25% or more of the light bulbs in the sample of 4400 are defective, the control unit calls repair technicians for service. Answer the following. (If necessary, consult a list of formulas.) (a)Find the mean of p, where p is the proportion of defective light bulbs in a sample of 4400 when there is no malfunction. (b)Find the standard deviation of p. (c)Compute an approximation for P≥p0.0125, which is the probability that the service technicians will be called even though the system is functioning properly. Round your answer to four decimal places.
The proportion p of residents in a community who recycle has traditionally been 60%. A policy maker claims that the proportion is less than 60% now that one of the recycling centers has been relocated. If 128 out of a random sample of 225 residents in the community said they recycle, is there enough evidence to support the policy maker's claim at the 0.05 level of significance? Perform a one-tailed test. Then complete the parts below. Carry your intermediate computations to three or more decimal places. A. State the null hypothesis H0 and the alternative hypothesis H1. H0: H1: B. Determine the type of test statistic to use. Is it (Z) (T) (Chi-square) or (F)? .
The proportion p of residents in a community who recycle has traditionally been 60%. A policy maker claims that the proportion is less than 60% now that one of the recycling centers has been relocated. If 128 out of a random sample of 225 residents in the community said they recycle, is there enough evidence to support the policy maker's claim at the 0.05 level of significance? Perform a one-tailed test. Then complete the parts below. Carry your intermediate computations to three or more decimal places. A. Find the value of the test statistic. (Round to three or more decimal places.) B. Find the critical value. (Round to three or more decimal places.) C. Is there enough evidence to support the policy maker's claim that the proportion of residents who recycle is less than 60%? (Yes or No)
This cardiologist gets a report on his patients' sugar consumption from the nutritionist. He becomes concerned that his patients seem to consume even more sugar that what is in a typical American diet. He decides to take a random sample of 100 of his patients and calculate the mean sugar consumption, x̅, of these 100 patients. The mean sugar consumption for these 100 patients is 17.3 teaspoons. Let's assume, for the moment, that his patients are no different than the general population of Americans with µ (daily sugar consumption) = 16.1 teaspoons and σ = 3.5 teaspoons and that his sample of 100 patients is one random sample from this population. What is the probability of obtaining a mean sugar consumption of 17.3 teaspoons (or more) in his sample of 100 patients if his patients are similar to the general population? What is the probability that the average (x̅) is greater than 17.3?

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