Source/Question Text Edits (#164)

* Edit Question Text

* Italicize Source

* Remove highlights with italics/bold

* Add Source to tables in Chapter 08

* Add italics to gt tables and remove from ggplot2

* Add missing text to Question text

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Co-authored-by: Stephanie Zimmer <[email protected]>

01-introduction.Rmd

@@ -111,7 +111,7 @@ Throughout the book, we use the following typographical conventions:
 
 ## Getting help
 
-We recommend first trying to resolve errors and issues independently using the tips provided in **Chapter \@ref(c12-recommendations)**. 
+We recommend first trying to resolve errors and issues independently using the tips provided in Chapter \@ref(c12-recommendations). 
 
 There are several community forums for asking questions, including:
 

03-survey-data-documentation.Rmd

@@ -21,10 +21,10 @@ Survey documentation can vary in organization, type, and ease of use. The inform
 
 The technical documentation, also known as user guides or methodology/analysis guides, highlights the variables necessary to specify the survey design. We recommend concentrating on these key sections:
 
-  * **Introduction:** The introduction orients us to the survey. This section provides the project's background, the study's purpose, and \index{Research topic|(}the main research questions.\index{Research topic|)}
-  * **Study design:** The study design section describes how researchers prepared and administered the survey.
-  * \index{Sampling error|(}\index{Sampling frame|(}\index{Sample|(}**Sample:** The sample section describes the sample frame, any known sampling errors, and limitations of the sample.\index{Sampling frame|)} \index{Weighting|(}This section can contain recommendations on how to use sampling weights. Look for weight information, whether the survey design contains strata, clusters/PSUs, or replicate weights. Also, look for population sizes, finite population correction, or replicate weight scaling information. Additional detail on sample designs is available in Chapter \@ref(c10-sample-designs-replicate-weights).\index{Sampling error|)}\index{Sample|)}\index{Weighting|)}
-  * **Notes on fielding:** Any additional notes on fielding, such as response rates, may be found in the technical documentation.
+  * Introduction: The introduction orients us to the survey. This section provides the project's background, the study's purpose, and \index{Research topic|(}the main research questions.\index{Research topic|)}
+  * Study design: The study design section describes how researchers prepared and administered the survey.
+  * \index{Sampling error|(}\index{Sampling frame|(}\index{Sample|(}Sample: The sample section describes the sample frame, any known sampling errors, and limitations of the sample.\index{Sampling frame|)} \index{Weighting|(}This section can contain recommendations on how to use sampling weights. Look for weight information, whether the survey design contains strata, clusters/PSUs, or replicate weights. Also, look for population sizes, finite population correction, or replicate weight scaling information. Additional detail on sample designs is available in Chapter \@ref(c10-sample-designs-replicate-weights).\index{Sampling error|)}\index{Sample|)}\index{Weighting|)}
+  * Notes on fielding: Any additional notes on fielding, such as response rates, may be found in the technical documentation.
 
 The technical documentation may include other helpful resources. For example, some technical documentation includes syntax for SAS, SUDAAN, Stata, and/or R, so we do not have to create this code from scratch.
 
@@ -64,7 +64,7 @@ knitr::include_graphics(path = "images/questionnaire-example-2.jpg")
 ### Codebooks
 
 \index{Missing data|(} \index{Codebook|(} \index{Data dictionary|see {Codebook}}
-While a questionnaire provides information about the questions posed to respondents, the codebook explains how the survey data were coded and recorded. It lists details such as variable names, variable labels, variable meanings, codes for missing data, value labels, and value types (whether categorical, continuous, etc.). The codebook helps us understand and use the variables appropriately in our analysis. In particular, the codebook (as opposed to the questionnaire) often includes information on missing data. Note that the term *data dictionary* is sometimes used interchangeably with codebook, but a data dictionary may include more details on the structure and elements of the data.
+While a questionnaire provides information about the questions posed to respondents, the codebook explains how the survey data were coded and recorded. It lists details such as variable names, variable labels, variable meanings, codes for missing data, value labels, and value types (whether categorical, continuous, etc.). The codebook helps us understand and use the variables appropriately in our analysis. In particular, the codebook (as opposed to the questionnaire) often includes information on missing data. Note that the term data dictionary is sometimes used interchangeably with codebook, but a data dictionary may include more details on the structure and elements of the data.
 \index{Missing data|)}
 
 \index{American National Election Studies (ANES)|(}