`r intToUtf8(c(50,46,48))`
This is the R Markdown outline for running inference, both a hypothesis test and a confidence interval. ##### Exploratory data analysis ###### Use data documentation (help files, code books, Google, etc.) to determine as much as possible about the data provenance and structure. ::: {.answer} Please write up your answer here ```{r} # Add code here to print the data ``` ```{r} # Add code here to glimpse the variables ``` ::: ###### Prepare the data for analysis. [Not always necessary.] ::: {.answer} ```{r} # Add code here to prepare the data for analysis. ``` ::: ###### Make tables or plots to explore the data visually. ::: {.answer} ```{r} # Add code here to make tables or plots. ``` ::: ##### Hypotheses ###### Identify the sample (or samples) and a reasonable population (or populations) of interest. ::: {.answer} Please write up your answer here. ::: ###### Express the null and alternative hypotheses as contextually meaningful full sentences. ::: {.answer} $H_{0}:$ Null hypothesis goes here. $H_{A}:$ Alternative hypothesis goes here. ::: ###### Express the null and alternative hypotheses in symbols (when possible). ::: {.answer} $H_{0}: math$ $H_{A}: math$ ::: ##### Model ###### Identify the sampling distribution model. ::: {.answer} Please write up your answer here. ::: ###### Check the relevant conditions to ensure that model assumptions are met. ::: {.answer} Please write up your answer here. (Some conditions may require R code as well.) ::: ##### Mechanics ###### Compute the test statistic. ::: {.answer} ```{r} # Add code here to compute the test statistic. ``` ::: ###### Report the test statistic in context (when possible). ::: {.answer} Please write up your answer here. ::: ###### Plot the null distribution. ::: {.answer} ```{r} # IF CONDUCTING A SIMULATION... set.seed(1) # Add code here to simulate the null distribution. ``` ```{r} # Add code here to plot the null distribution. ``` ::: ###### Calculate the P-value. ::: {.answer} ```{r} # Add code here to calculate the P-value. ``` ::: ###### Interpret the P-value as a probability given the null. ::: {.answer} Please write up your answer here. ::: ##### Conclusion ###### State the statistical conclusion. ::: {.answer} Please write up your answer here. ::: ###### State (but do not overstate) a contextually meaningful conclusion. ::: {.answer} Please write up your answer here. ::: ###### Express reservations or uncertainty about the generalizability of the conclusion. ::: {.answer} Please write up your answer here. ::: ###### Identify the possibility of either a Type I or Type II error and state what making such an error means in the context of the hypotheses. ::: {.answer} Please write up your answer here. ::: ##### Confidence interval ###### Check the relevant conditions to ensure that model assumptions are met. ::: {.answer} Please write up your answer here. (Some conditions may require R code as well.) ::: ###### Calculate and graph the confidence interval. ::: {.answer} ```{r} # Add code here to calculate the confidence interval. ``` ```{r} # Add code here to graph the confidence interval. ``` ::: ###### State (but do not overstate) a contextually meaningful interpretation. ::: {.answer} Please write up your answer here. ::: ###### If running a two-sided test, explain how the confidence interval reinforces the conclusion of the hypothesis test. [Not always applicable.] ::: {.answer} Please write up your answer here. ::: ###### When comparing two groups, comment on the effect size and the practical significance of the result. [Not always applicable.] ::: {.answer} Please write up your answer here. :::