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.

Credit Card Transactions:

September26: Credit card payment $9,000.

September28: Paid net wages to 4 employees @$1082 each after withholding tax of @$118 per employee. Guaranteed super is 9.5% on gross salary. You will mention the name of each employed as a payee.

September 28: Received Electricity bill $231 including GST. The bill is not yet paid.

September 30: Bank charged account fees $10.        

1. Prepare Profit and Loss Statement for the month ended on 30th September2020 and Balance Sheet at 30th September2020.

Warnerwoods Company uses a perpetual inventory system. It entered into the following purchases and sales transactions for March.
  

4. Compute gross profit earned by the company for each of the four costing methods. For specific identification, the March 9 sale consisted of 80 units from beginning inventory and 340 units from the March 5 purchase; the March 29 sale consisted of 40 units from the March 18 purchase and 120 units from the March 25 purchase. (Round weighted average cost per unit to two decimals.)
  

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.

1.       A   university   researcher   is   interested   in   whether   recent   recruitment   efforts   have   changed   the   type   of   students   admitted   to   the   university.   To   test   this,   she   randomly   selects   50   freshmen   from   the   university   and   records   their   high   school   GPA.   The   mean   is   2.90   with   a   standard   deviation   of   0.70.   The   researcher   also   knows   that   the   mean   high   school   GPA   of   all   freshmen   enrolled   at   the   university   five   years   ago   was   2.75   with   a   standard   deviation   of   0.36.   The   researcher   wants   to   know   if   the   high   school   GPA   of   current   freshmen   at   the   university   is   different   than   that   of   freshmen   from   five   years   ago.  
   (a)   What   are   the   null   and   alternative   hypotheses   in   this   study   (stated   mathematically)?  
   (b)   Should   the   researcher   use   a   one-tailed   or   a   two-tailed   test?  
   (c)   Compute   the   appropriate   test   statistic   for   testing   the   hypothesis.  
   (d)   Using   α   =   0.05,   what   do   you   conclude   about   the   high   school   GPA   of   current   freshman?   Be   sure   to   include   a   discussion   of   the   critical   value   in   your   answer.  
   (e)   What   type   of   error   might   the   researcher   be   making   in   part   (d)?  
  
   2.   A   researcher   believes   that   smoking   worsens   a   person’s   sense   of   smell.   To   test   this,   he   takes   a   sample   of   25   smokers   and   gives   them   a   test   of   olfactory   sensitivity.   In   this   test,   higher   scores   indicate   greater   sensitivity.   For   his   sample,   the   mean   score   on   the   test   is   15.1   with   a   standard   deviation   of   1.2.   The   researcher   knows   the   mean   score   in   the   population   is   15.5,   but   the   population   standard   deviation   is   unknown.  
   (a)   What   are   the   null   and   alternative   hypotheses   in   this   study   (stated   mathematically)?  
   (b)   Should   the   researcher   use   a   one-tailed   or   a   two-tailed   test?  
   (c)   Compute   the   appropriate   test   statistic   for   testing   the   hypothesis.  
   (d)   Using   α   =   0.01,   do   you   conclude   that   smoking   affects   a   person’s   sense   of   smell?   Be   sure   to   include   a   discussion   of   the   critical   value   in   your   answer.  
   (e)   What   type   of   error   might   the   researcher   be   making   in   part   (d)?