At Burnt Mesa Pueblo, archaeological studies have used the method of tree-ring dating in an effort to determine when prehistoric people lived in the pueblo. Wood from several excavations gave a mean of (year) 1239 with a standard deviation of 43 years. The distribution of dates was more or less mound-shaped and symmetrical about the mean. Use the empirical rule to estimate the following.

(a) a range of years centered about the mean in which about 68% of the data (tree-ring dates) will be found
between  and  A.D.

(b) a range of years centered about the mean in which about 95% of the data (tree-ring dates) will be found
between  and  A.D.

(c) a range of years centered about the mean in which almost all the data (tree-ring dates) will be found
between  and  A.D.

Young Professional magazine was developed for a target audience of recent college graduates who are in their first 10 years in a business/professional career. In its two years of publication, the magazine has been fairly successful. Now the publisher is interested in expanding the magazine’s advertising base. Potential advertisers continually ask about the demographics and interests of subscribers to Young Professional. To collect this information, the magazine commissioned a survey to develop a profile of its subscribers. The survey results will be used to help the magazine choose articles of interest and provide advertisers with a profile of subscribers. As a new employee of the magazine, you have been asked to help analyze the survey results which had a sample size of 410. The data is summarized below: Quantitative Variables Mean Standard Deviation Age 30.112 4.024 Household Income $74,460 $34,818 Qualitative Variables Count Broadband Access Yes: 256 Have Children Yes: 219 a. Develop 95% confidence intervals for the mean age and household income of subscribers. b. Develop 95% confidence intervals for the proportion of subscribers who have broadband access at home and the proportion of subscribers who have children. c.Would Young Professional be a good advertising outlet for online brokers?Justify your conclusion with statistical data.please provide detailed solution

For this problem, collect data on any variables of interest (sample size for each group of the two groups n=>30) and perform a two-sided significance test for comparing two independent population means. You can also simulate your own data. Address the following:

a. A brief introductory paragraph describing the problem. Remember that you want to think of an experiment where you’re comparing 2 independent groups, such as, for example, “the population mean speed for runners using training method A versus runners using training method B.” There is a clinical trial of a drug that is supposed to significantly reduce you cholesterol and the two groups

b. Set up your framework in a null and alternative hypothesis using symbols and notation as they are presented in the textbook. For the null, traditionally should have the general set-up of H0: µ1 = µ2 An example of this could be “µA = the population mean speed for runners using method A is equal to µB = the population mean speed for runners using method B.” H1: can have a <, or >, or ≠ depending on what you choose to test. Using the example above, if you want to test that A is greater than B, then do: H1: µA > µB

c. A paragraph describing how you collected the data (i.e., the number of observations, time of day, etc. Please present the raw data in a table.

d. Create a graph of the means of the two samples using Excel. Clearly label your axes, and give your figure a title.

e. A section explaining the results of the analysis (calculated statistics, and p-values). Based on what you find, state your decision (whether you reject or fail to reject the H0) and conclusion (whether you have sufficient or insufficient evidence for H1).

f. Describe how would you change the experimental design to become dependent or related samples? Think about which factors you could possibly control for that weren’t controlled for in the initial analysis. For example, instead of comparing 2 independent groups of runners using method A vs. B, we could “match” runners across groups according to age, experience, education, height, etc. This approach is more complicated, but worth describing how it could be done.

A survey was conducted to study if parental smoking is associated with the incidence of smoking in children when they reach high school. Randomly chosen high school students were asked whether they smoked and whether at least one of their parents smoked.

The results are summarized in the following table:

Student Smoke Student Don’t

Parents Smoke 262 183

Parents Don’t 120 380

(a) For a randomly selected student in this study, find the conditional probability of smoking given his/her parents smoke.

(b) Suppose we are interested in testing whether parental smoking is independent of children smoking. Which statistical test would you consider for this problem?

(c) (4 points) Write down the R code to carry out that test. You first need to store the data into a matrix.

(d) Calculate the test statistic by yourself.

(e) Write down the R code to obtain the p-value based on your answer in
part(d).
(f) Suppose the p-value is 0.0001, what would be your really world conclusion? (You may use α = 0:05.)

what is the generalizability in the study on maternal health care quality indicator?

A researcher is testing the claim that adults consume an average of at least 1.85 cups of coffee per day. A sample of 35 adults shows a sample mean of 1.70 cups per day with a sample standard deviation of 0.4 cups per day. Test the claim at a 5% level of significance. What is your conclusion?

*Please explain each step, I just don't get it

How do you determine the slope of a line? Is there more than one way to determine the slope? Why or Why not? How do you find the intercepts of a line? Explain using an example.

Salaries of 32 college graduates who took a statistics course in college have a​ mean,x overbarx​,of $ 65,300. Assuming a standard​ deviation,sigmaσ​,of​$13,299​,construct a 95​% confidence interval for estimating the population mean muμ.

​$nothingless than<muμless than<​$nothing

​(Round to the nearest integer as​ needed.)

Should one always select the decision path that has the highest expectation value? Why/Why not? Give an example where one might not.

In the sports industry what types of questions could you ask and assess using linear regression?

Is the bottled water you are drinking really purified water? In a four-year study of bottled water brands conducted by the Natural Resources Defense Council found that 25% of bottled water is just tap water packed in a bottle. Consider a sample of five brands of bottled water and let X equal the number of these brands that use tap water.

1. Explain why X is (approximately) a binomial random variable.

2. Find that the P (x = 2)

3. Find that the P (x <= 1)

4. Calculate the expected value and standard deviation of the distribution.

A sample of 15 measurements, randomly selected from a normally distributed population, resulted in a sample mean, x¯¯¯=6.1 and sample standard deviation s=1.92. Using α=0.1, test the null hypothesis that μ≥6.4 against the alternative hypothesis that μ<6.4 by giving the following.

a) The number of degrees of freedom is: df= .

b) The critical value is: tα= .

c) The test statistic is: ttest=

Suppose you were asked to investigate which predictors explain the number of minutes that 10- to18-year-old students spend on Twitter. To do so, you build a linear regression model with Twitter usage (Y) measured as the number of minutes per week. The four predictors you include in the model are Height, Weight, Grade Level, and Age of each student. You build four simple linear regression models with Y regressed separately on each predictor, and each predictor is statistically significant. Then you build a multiple linear regression model with Y regressed on all four predictors, but only one predictor, Age, is statistically significant, and the others are not. What is likely going on among the four predictors? If you include more than one of these predictors in the model, what are some problems that can result?

3. In the following situations, identify the random variable of interest (e.g. ”Let X be the number of ...”). Then state whether or not the r.v. is binomial, justifying your answer.

(a) A police officer randomly selects 30 cars to find out how many do not have

a current Warrant of Fitness (WOF). She knows from experience that the

probability a car does not have a current WOF is 1.6

(b) A data collector goes from house to house in a Wellington suburb to find the number of houses where the person answering the door (over the age of 18) agrees with a particular housing policy of the current government. The probability that a randomly selected adult in New Zealand agrees with the policy is known to be 0.4. The collector will stop collecting responses once they have 100 responses.

(c) Mike is repeatedly rolling two dice and will stop when he gets a double six. He counts the number of rolls until he gets a ’success’.