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"m*U]w3}#2{v#j>:dEsYWAz[##M,*p#vn#ydk+yR[z##&Y$ E #V#J|FxJ5#v#URCM(>r#"!t :IQ! }#J#Tu#('5#2H&S#Rxt##h%#Z#m'#k#c#q#Ma#X#+#EEJ7 < 54###.#.6)5#4q}z#\\HZ\\o#J|#] +n&BIi##).$##.#]ju=ZRMgsHT;Z%u#-@k&#N0r7 t`x&RSz#mI!1[#6ywa~T4E#M^#dW&0scM ? 3%# %fvKe#,p<3B#'y#\\p|#U#o##QYZi-1 rN}1T#W [#.)'Xk9ql?,z:Pu,% ##y[zn %71Ao@;HEb0${=N<1#v c[~#3N?@?VOe#bP]#x Mj{r##Y#QcU#K[-/Y1#:{##Bdl#W[i5&#^##;~;"f< ######################################################################D#i# a#l#o#g#s#################################D#i#a#l#o#g#s################# ################################################ ################<#######O###,###################9########################### ################################################################################ ###################################### ###,###############S#t#a#t#e#V#a#r#i#a#b#l#e#s#################,###############S #t#a#t#e#V#a#r#i#a#b#l#e#s################# ##### #######################################################0###############G #l#################################################################o#b#a#l#A#t#t #r#i#b#u#t#e#s#################0###############G#l#o#b#a#l#A#t#t#r#i#b#u#t#e#s## ############### ############################# ###############################2###############M#i#n#i#t#a#b# #-# #B#A#C#.#M#P#J#################################################b ##########j###I{#GzTI{#GzT9? p= ?#@?######## ###&###############P#r#o#j#e#_################################################## ######## ############;###oo;.?h##^+DRq_sr9[|#\\o## #_S'?c> q# qk#pz+8huA##^~K}d~?vl]X %X#CX#1e##AFU7v#Y}u7# [a/f}0: G#t##I #&3J Jkpivvj##jP#HHNd#c##\\iR+# A#l]rC\\Fh#m 86?>u2c#j#X!g?U#`~>, 5G##X###y##I\\#`,#9;^+my#;#uy(;EQKyo# KP/t|#nu[##`m}C33# ##G###################################################################### ################################################################################ ################################################################################ ################################################################################ ######################################################################### 12/27/13 Thinking outside the margin - Web Exclusive Article - Significance Magazine Significance - Statistics making sense Thinking outside the margin Ian McCarthy I recently came across an online article for TIME magazine titled \"Is the Economy Making You Fat?\" - a testament that the economy literally can be blamed for anything. The article discussed some new findings of the National Bureau of Economic Research which estimated a 4% decrease in fruit and vegetable consumption in response to a 1% increase in the local unemployment rate. Although I commend the author for his pulse on recent economic literature, his interpretation of the results exemplifies an unfortunate divide between those doing the research and those reporting the results to the public. I blame our schools. Does a decrease in jobs mean an increase in sales of these? Image from Wiki Commons I'll limit my concern to a couple of points. First, the author justifies this relationship in a way we can all understand. \"Losing your job tends to lead to depression and other mental ailments. As a result, people tend to spend less time worrying ab out their health, and more time compensating with junk food.\" Never mind the heap of literature on the relationship between household income and the purchase of cheaper (usually less healthy) foods. I'll forgive him for this one since the \"rational economic agent\" rarely sells. More egregiously, the author extends the results to values well beyond anything in the underlying research (which covered the years 1999 through 2007): \"In the past few years, the national unemployment rate has risen from 4.4% in late 2006 to a recent 9.8%. As a result, we may b e eating as much as 22% fewer fruits and vegetab les.\" This conclusion derives from a huge, nearly unprecedented jump in unemployment (4.4% to 9.8%). The research found a marginal effect, but the article's author applied the marginal effect to a huge change in unemployment. Regression results are not made to be treated in such ways. They behave nicely so long as we stay within a reasonable range of the data, but may fall apart if we venture too far away. References "Is the Economy Making You Fat" Dave, D. and I. Kelly (2010). \"How Does the Business Cycle Affect Eating Habits?\" NBER Working Paper No. 16638. www.significancemagazine.org/details/webexclusive/981803/Thking-outside-the-margin.html 1/2 12/27/13 Thinking outside the margin - Web Exclusive Article - Significance Magazine Published by Blackwell Publishing Ltd, a company of John Wiley & Sons, Inc. About Us Contact Us Newsletters Privacy Policy Accessibilty Policy www.significancemagazine.org/details/webexclusive/981803/Thking-outside-the-margin.html Terms & Conditions 2/2 The answers I have are highlighted in yellow. The data L4HW2.MPJ is for minitab. I am stuck on questions 4-7 The data set for this assignment is labeled L4HW2. It contains data on Blood Alcohol Content (BAC) for a set of men who drank a particular number of beers over a one hour period. We wish to predict BAC from the number of beers consumed using simple regression. The commands you need are under Stat>Regression. To do a prediction, click on the "Options" box in the regression command. Type the value of the X variable into the box "Prediction Intervals for new observations." Question 1 1 pts The correlation between BAC and Beers is 0.894 (three decimal places). Question 2 3 pts Using Minitab, regress BAC (the response or dependent variable) on Beers (the explanatory or independent variable). Round answers to three decimal places. The intercept is: -0.013 the slope is: 0.018 and the correlation coefficient is: 0.894 Question 3 3 pts Person 4 drank 8 beers and had a BAC of 0.120. Round answers to three decimal places. His observed BAC was 0.120 and his expected (or predicted) BAC was 0.131 The residual for this person was -0.011 Question 4 1 pts What is the expected average BAC for a person who has 5 drinks? 0.077 Question 5 1 pts What is the expected average BAC for a person who drinks 20 beers? (Round to three decimal places) 0.347 (Note this value is an outlier) Read the short article, "Thinking Outside the Margin," also available under Content>Articles. The rest of the questions pertain to this article. Question 6 1 pts The article's authors estimated "a 4% decrease in fruit and vegetable consumption in response to a 1% increase in the local unemployment rate." Does this provide evidence that the rise in unemployment caused a decline in fruit and vegetable consumption? 1. Yes, because the regression results were statistically significant. 2. No, because the regression results were not statistically significant. 3. Yes, because the regression results were statistically significant and also made sense. 4. No, because regression results can never be given causal interpretation. Flag this Question Question 7 1 pts The author of the TIME article used the results of the study to predict a 22% decline in fruit and vegetable consumption during the recent recession. Why is this reasoning faulty? 1. The results were not statistically significant, so you can't use them to make predictions. 2. The rise in unemployment was larger than normal, and was out of the range of the data used for the prediction. Hence, the author was making an interpolation too large to be supported by the analysis. 3. The number just doesn't make sense; 22% is too big a decline. 4. The rise in unemployment was not as big as they said it was, so the prediction is incorrect. The answers I have are highlighted in yellow. The data L4HW2.MPJ is for minitab. I am stuck on questions 4-7 The data set for this assignment is labeled L4HW2. It contains data on Blood Alcohol Content (BAC) for a set of men who drank a particular number of beers over a one hour period. We wish to predict BAC from the number of beers consumed using simple regression. The commands you need are under Stat>Regression. To do a prediction, click on the "Options" box in the regression command. Type the value of the X variable into the box "Prediction Intervals for new observations." Question 1 1 pts The correlation between BAC and Beers is 0.894 (three decimal places). Question 2 3 pts Using Minitab, regress BAC (the response or dependent variable) on Beers (the explanatory or independent variable). Round answers to three decimal places. The intercept is: -0.013 the slope is: 0.018 and the correlation coefficient is: 0.894 Question 3 3 pts Person 4 drank 8 beers and had a BAC of 0.120. Round answers to three decimal places. His observed BAC was 0.120 and his expected (or predicted) BAC was 0.131 The residual for this person was -0.011 Question 4 1 pts What is the expected average BAC for a person who has 5 drinks? 0.077 Question 5 1 pts What is the expected average BAC for a person who drinks 20 beers? (Round to three decimal places) 0.347 (Note this value is an outlier) Read the short article, "Thinking Outside the Margin," also available under Content>Articles. The rest of the questions pertain to this article. Question 6 1 pts The article's authors estimated "a 4% decrease in fruit and vegetable consumption in response to a 1% increase in the local unemployment rate." Does this provide evidence that the rise in unemployment caused a decline in fruit and vegetable consumption? 1. Yes, because the regression results were statistically significant. 2. No, because the regression results were not statistically significant. 3. Yes, because the regression results were statistically significant and also made sense. 4. No, because regression results can never be given causal interpretation. Flag this Question Question 7 1 pts The author of the TIME article used the results of the study to predict a 22% decline in fruit and vegetable consumption during the recent recession. Why is this reasoning faulty? 1. The results were not statistically significant, so you can't use them to make predictions. 2. The rise in unemployment was larger than normal, and was out of the range of the data used for the prediction. Hence, the author was making an interpolation too large to be supported by the analysis. 3. The number just doesn't make sense; 22% is too big a decline. 4. The rise in unemployment was not as big as they said it was, so the prediction is incorrect