Following to questions answer the following:

- Provide the null and alternative hypotheses with the appropriate symbols.

- The significance level of the test. If it is not given use a significance level of 0.05.

- The P-value for the test. State whether you reject or fail to reject the null hypothesis. In other words, compare the P-value to the significance level to decide whether to reject or fail to reject the null hypothesis.

Question 1:

The body mass index or BMI of an individual is a measure used to judge whether an individual is overweight . A BMI between 20 and 25 indicates a normal weight. In a survey of 750 men and 750 women, the Gallup organization found that 203 men and 270 women were normal weight. Using a significance level of 0.10, determine whether there is a difference in the proportion of men compared the proportion of women who are normal weight.

Question 2:

In a Gallup poll, 513 national adults who consider themselves to be Democrat were asked, "Of every tax dollar that goes to the federal government, how many cents of each dollar would you say are wasted?" The sample mean for the Democrats was found to be 41 cents with a sample standard deviation of 2.6 cents. The same question was asked of 513 national adults who consider themselves to be Republican. The sample mean for the Republicans was found to be 54 cents with a standard deviation of 2.9 cents. Use this information to determine if Democrats believe fewer tax dollars are wasted compared to Republicans.

The following transactions were selected from the records of Evergreen Company: July 12 Sold merchandise to Wally Butler, who paid for the $1,000 purchase with cash. The goods cost Evergreen Company $600. 15 Sold merchandise to Claudio’s Chair Company at a selling price of $5,000 on terms 3/10, n/30. The goods cost Evergreen Company $3,500. 20 Sold merchandise to Otto’s Ottomans at a selling price of $3,000 on terms 3/10, n/30. The goods cost Evergreen Company $1,900. 23 Collected payment from Claudio’s Chair Company from the July 15 sale. Aug. 25 Collected payment from Otto’s Ottomans from the July 20 sale. Required: Prepare journal entries to record the transactions, assuming Evergreen Company uses a perpetual inventory system.

Is there a linear relationship between the obesity rates and infant mortality for countries in the Global Health Summary data set? Investigate the relationship between obesity rates and infant mortality by using StatCrunch and complete the parts below.

1. Use the Simple Linear Regression feature in StatCrunch to construct the regression model and scatterplot to compare the obesity rate (x-variable) to the infant deaths per 1000 (y-variable). Insert the results in the space below. (TIP: You need to insert both the linear regression information and the scatterplot.)

<insert graphic here>

2. Report the correlation coefficient (r) and write the equation for the linear relationship as ____Locate the critical value for correlation coefficients with a sample size of thirty or higher. (If necessary, round your answers to the nearest hundredth.)

3. Determine if there is a valid linear relationship between obesity rates and infant mortality rates. To receive full credit, your answer should make use of the correlation coefficient and the critical value. If there is a linear relationship, describe how the two variables are related.

4. Would it be appropriate to conclude a cause-and-effect relationship between obesity rates and infant mortality rates? Explain why or why not.

5. Identify at least one confounding or lurking variable and describe how it may be related to obesity rates and infant mortality rates. (Tip: You will need to think beyond the data set for this question.)

Is there a linear relationship between the obesity rates and infant mortality for countries in the Global Health Summary data set? Investigate the relationship between obesity rates and infant mortality by using StatCrunch and complete the parts below.

1. Use the Simple Linear Regression feature in StatCrunch to construct the regression model and scatterplot to compare the obesity rate (x-variable) to the infant deaths per 1000 (y-variable). Insert the results in the space below. (TIP: You need to insert both the linear regression information and the scatterplot.)

<insert graphic here>

2. Report the correlation coefficient (r) and write the equation for the linear relationship as ____Locate the critical value for correlation coefficients with a sample size of thirty or higher. (If necessary, round your answers to the nearest hundredth.)

3. Determine if there is a valid linear relationship between obesity rates and infant mortality rates. To receive full credit, your answer should make use of the correlation coefficient and the critical value. If there is a linear relationship, describe how the two variables are related.

4. Would it be appropriate to conclude a cause-and-effect relationship between obesity rates and infant mortality rates? Explain why or why not.

5. Identify at least one confounding or lurking variable and describe how it may be related to obesity rates and infant mortality rates. (Tip: You will need to think beyond the data set for this question.)

Is there a linear relationship between the obesity rates and infant mortality for countries in the Global Health Summary data set? Investigate the relationship between obesity rates and infant mortality by using StatCrunch and complete the parts below.

1. Use the Simple Linear Regression feature in StatCrunch to construct the regression model and scatterplot to compare the obesity rate (x-variable) to the infant deaths per 1000 (y-variable). Insert the results in the space below. (TIP: You need to insert both the linear regression information and the scatterplot.)

<insert graphic from StatCrunch here>

2. Report the correlation coefficient (r) and write the equation for the linear relationship as ____Locate the critical value for correlation coefficients with a sample size of thirty or higher. (If necessary, round your answers to the nearest hundredth.)

3. Determine if there is a valid linear relationship between obesity rates and infant mortality rates. To receive full credit, your answer should make use of the correlation coefficient and the critical value. If there is a linear relationship, describe how the two variables are related.

4. Would it be appropriate to conclude a cause-and-effect relationship between obesity rates and infant mortality rates? Explain why or why not.

5. Identify at least one confounding or lurking variable and describe how it may be related to obesity rates and infant mortality rates. (Tip: You will need to think beyond the data set for this question.)

Is there a linear relationship between the obesity rates and infant mortality for countries in the Global Health Summary data set? Investigate the relationship between obesity rates and infant mortality by using StatCrunch and complete the parts below.

1. Use the Simple Linear Regression feature in StatCrunch to construct the regression model and scatterplot to compare the obesity rate (x-variable) to the infant deaths per 1000 (y-variable). Insert the results in the space below. (TIP: You need to insert both the linear regression information and the scatterplot.)

<insert graphic from StatCrunch here>

2. Report the correlation coefficient (r) and write the equation for the linear relationship as ____Locate the critical value for correlation coefficients with a sample size of thirty or higher. (If necessary, round your answers to the nearest hundredth.)

3. Determine if there is a valid linear relationship between obesity rates and infant mortality rates. To receive full credit, your answer should make use of the correlation coefficient and the critical value. If there is a linear relationship, describe how the two variables are related.

4. Would it be appropriate to conclude a cause-and-effect relationship between obesity rates and infant mortality rates? Explain why or why not.

5. Identify at least one confounding or lurking variable and describe how it may be related to obesity rates and infant mortality rates. (Tip: You will need to think beyond the data set for this question.)

In 2016, the World Health Organization estimated that the average life expectancy at birth worldwide was 72 years[1]. (This includes all countries of the world, not just the countries in the sample.)

Complete the steps below to carry out a one-mean hypothesis test to test the claim that the average life expectancy has increased beyond the global average using a 5% significance level.

Let mean = the average life expectancy of a person at birth (globally).

1. State your Null and Alternative Hypothesis symbolically. (You may need to copy and paste symbols.)
2. Verify that the conditions of the one-mean hypothesis test are satisfied.

3. calculate the test statistic and p-value. Round your answer to the nearest thousandth. Insert the results from the hypothesis test from StatCrunch in the space provided.

Test Statistic:

p-value:

4. Determine if you should Reject null hypothesis or fail to reject the null hypothesis. Use the significance level and your p-value to explain how you made your decision.

5. Using sentences, write your conclusion using the context of the problem.

[1] Source: World Health Organization.

1. List the 4 phases of the business cycle.

Which phase are we in right now?

What evidence do you have to support your theory?

Describe who is in the labor force.

Who is not included in the labor force. In the past 20 years or so, the baby boom generation has been retiring. It is estimated that 10,000 turn 65 years old every day in the US. In addition, record numbers of workers gave up looking for jobs in the 2008-09 recession. How do these demographic and cultural changes affect the unemployment rate?

The distribution of weights for 12 month old baby girls in the US is approximately normal with mean u = 21 pounds and standard deviation of 2.2 pounds.

a) if a 12 month old girl weighs 23.2 pounds, approximately what weight percentile is she in?

b) if a 12 month old girl is in the 16th percentile in weight, estimate her weight.

c) Estimate the weight of t 12 month old girl who is in the 25th percentile by weight.

d) Estimate the weight of a 12 month old girl who is in the 75th percentile by weight.

1. Identify three applications of information systems at the college or the university that you are attending. Write three applications, and provide an example of the type of decisions that are being improved by each application.

2.  RFID tags are being increasingly used by companies such as Macy's, Walmart, and Home Depot. Identify an additional company that uses RFIDs and describe the company’s specific application of RFIDs.