Fixes #107. No longer excludes samples with p_hat =0 #108
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The call to filter(scientist_work == "Doesn't benefit") is filtering out any replicates where there are no "Doesn't benefit"s in the small sample. As a result any replicates with p_hat=0 are filtered out and are not displayed. This issue is caused by using a small sample size and a true proportion close to 0 (p=.2). I have replaced this filtering code with the following group_by(replicate)%>% summarize(p_hat = mean(scientist_work=="Doesn't benefit")) Fixes OpenIntroStat#107.
Replaces code based on filtering (which breaks down in the edge case where teh sample proporiton is 0, since there is then nothing to filter on) with code based on group_by + summarize.
…he lab to crash: "Quitting from lines 70-76 (inf_for_categorical_data.Rmd) Warning: Error in : A proportion is not well-defined for a multinomial categorical response variable (text_ind) and no explanatory variable." text_ind contained "NA"s in addition to "yes"s and "no"s. This commit filters to complete cases (to eliminate the "NA"s).
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The call to
filter(scientist_work == "Doesn't benefit")
is filtering out any replicates where there are no "Doesn't benefit"s in the small sample. As a result any replicates with p_hat=0 are filtered out and are not displayed.
This issue is caused by using a small sample size and a true proportion close to 0 (p=.2).
I have replaced this filtering code with the following
group_by(replicate)%>% summarize(p_hat = mean(scientist_work=="Doesn't benefit"))
Fixes #107.