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K7#Hg#O#7#?|x ## ##mb## # ##Yu#[I>dO# ##o# #s9#'6GD###<.# ##y#hG##y#xFFG####z# #0D#=(L###x#O#@W%####_ ]##_#okSoX;z#;###i[+9+ a?ES?Wx?##=#z?_~# #9Kt#|7}z/9?)w6[L#[+FdL[)?_3 1O* #y:ip3E]}ji#c#c5m#Y0v#tI9 }Y#;r4n#K_*[G6 UyZ;:StLu<#>#{w#A#A<R N? jpzDu`yj\\j_:Ax13uu9#w>s>#_mtw#x(u/rwO#1Vw 5~Ww/gTyg###>#u||?;(~O} {=:#gW//s,Nt:~R*##:#7b#.`Oy #N E#M#Hbf#u].Uj#VC)?d\\o~2-i*i_###E>")Ff#{#04-v51 {Q<#_L;#Y~q 1##hI#f<#qJ N d##rQ@$ d~##}? 0|7#N##* %ey;;### ############################################# ################ R#o#o#t# #E#n#t#r#y############################################################## ####################:f##############W#o#r#k#s#h#e#e#t#D#a#t#a#1#7############ ####################### ###########################################1#######W#o#r#k#s#h#e#e#t #I#n#f#o#################################################################### ################### ##########C#o#m#p#r#e#s#s#e#d################################################# #########################:f###:f################################### ########### ####### ########################################################################### 1###############W ORK####N###############V#:#\\#D#e#s#k#t#o#p#\\#L#a#b#0#6#_#P#H#a#t#V#a#l#u#e#s#.#m #t#w#8###############L#a#b#0#6#_#P#H#a#t#V#a#l#u#e#s#.#m#t#w#################### ########################################################## ### ######### @ ###############S#e#g#o#e# #U#I#2###############S#e#g#o#e# #U#I# #S#e#m#i#b#o#l#d#################*######ADDR##### ###CmColumnVar#ADDRf#### ###CmColumnVar#####################{#####################N########\\############ ###################<########################### ##################################################_############################# ############################# ############;###P#::O## #H##?#.On Ad#QYC,,S-#p####################### LAB ACTIVITY 6 Due Friday, Sept. 30 at 11:59pm (Use 'ClassData_FA2016.mtw' dataset) Activity 1: Types of bias in surveys. Penn State Pulse conducts a survey about the frequency of academic cheating. Identify each of following as an example of non-participation, selection, or response bias. a. If the sample used in the survey is selected from a list of Penn State football season ticket holders. b. If those who cheat a lot refuse to answer questions. c. If those who cheat a lot lie about their cheating. Activity 2: Statistics experiment using confidence intervals In this activity, you will pool information with the other students in the class. a. In Minitab, use the File menu to create a new worksheet. b. Now use Minitab to create 400 rows of randomly chosen zeros and ones, where the true probability of a one equals 60%. To do this, select Calc Random Data Bernoulli. (The \"Bernoulli distribution\" refers to randomly generated zeros and ones, just like yeses and nos randomly sampled from a large population of people who might be asked a yes/no question.) Next, fill in 400 for the number of rows. Store in column C1, and type 0.6 for event probability. Then click OK. c. You should have 400 rows of 1 and 0 in column C1. You can imagine that 1 stands for one type of response to a question, and 0 stands for the other type (we're assuming we've got a question where we can somehow group the answers into just two types). Use Stat Tables Tally Individual Variables to obtain the counts of 0 and 1 in the C1 column. Copy and paste the text that gives the counts. d. Use the information from part c to calculate the sample proportion of ones. Report your sample proportion to your TA, who will keep track of all the sample proportions for your lab section. (You must be present in lab to receive credit for this question.) e. Calculate the margin of error for a 95% confidence interval using the formula we've seen in class. Use it to construct a confidence interval for the true proportion. f. In this experiment (unlike in a typical real-world application), we actually know the true proportion. Does your confidence interval contain it? NB: Not all intervals will contain the true population parameter, but the hope is that most of the time they will! g. (Wait until Friday's class to answer.) How many sample proportions are in your lab section, and how many of them lead to confidence intervals that contain the true proportion? h. (Wait until Friday's class to answer.) Look at a histogram of all the sample proportions from your lab section. Describe the shape of the histogram, and estimate the mean and standard deviation. (For the SD, use the trick we saw in lecture: Take the width of roughly the middle 95% of the histogram, then divide this width by four.) Activity 3: Conservative margin of error and confidence interval for real data Suppose we choose a sample of 289 Penn State students (the members of this STAT 200 class will be the sample, and the sample responses are in the ClassData_FA2016.mtw dataset). We are interested in the proportion of Penn State students who walk from home to campus for class. (a) First find the sample proportion. (b) Next, find the conservative margin of error using the formula we've seen in lecture. (c) Now find an interval that covers the true population proportion with 95% confidence and write a sentence interpreting it. Activity 4: 1. To estimate the percentage of households in the US that use a DVD player, a researcher surveys a randomly selected sample of 1000 households and asks about DVD player usage. a. What is the population of interest for this survey? b. What is the sample in this survey? 2. Decide whether the margin of error would increase, decrease, or remain the same for each of the changes below. Assume that each time we have a random sample. a. Increase sample size from 1000 to 4000. b. Decrease sample size from 1000 to 250. c. Increase the population size from 10 million to 20 million. 3. Suppose that we wanted to construct a confidence interval whose margin of error was 3%. How large a sample would be necessary for this