Here are a few more TIPS for you to consider. They reflect some additional concerns I have regarding the last group of BSFs I reviewed. Please carefully review these recommendations and incorporate them into future BSFs when it's relevant. As always, see me with any questions.
1. For organizational purposes, in any univariate analysis section of a report, provide your descriptive analysis (means, standard deviations, percentage breakdowns, etc.) of the independent variables before you begin your singular analysis and discussion of the dependent variable(s).
2. When it comes to missing data (i.e., “refusals,” “don’t knows,” “no answers,” “not applicables,” etc.) associated with a univariate or bivariate analysis, unless you’re asked to do so, you need not report when one person or a non-trivial number of persons refuse to answer a survey item. By focusing on the VALID PERCENT column, with properly assigned missing cases, SPSS removes (excludes) those missing cases from the column for a “clean” interpretation of the results. In national surveys, such as those conducted by the National Opinion Research Center (NORC), people who do not respond to an item generally do not invalidate either the entire survey or any subset of variables analyzed within it.
3. Some students have incorrectly introduced the term “correlation” in our first BSF in the following way: “From the results, I cannot see any correlation between X and Y.” As we will soon discover in class, a correlation is a statistical measure of the strength of the relationship between at least an ordinal level X and Y and should only be used in that context. To use the term as a synonym for “relationship” or “association” would, therefore, be incorrect when conducting a crosstabular analysis.
4. The integration of tables and charts, while previously discussed in class and at this blog, needs additional clarification. Never place a table or chart in the center of your text discussion – only to the right (with discussion on the left) or, preferably, below the relevant discussion. Moreover, always label a table within its title (e.g., “TABLE 1C: Gender of MBA Students by Attitudes Toward Management Scores”) and reference the table/chart in your text as previously described (i.e., “See TABLE 1C”). Any unlabeled table or chart, whether referenced or not somewhere in your analysis, does not belong in the report.
5. When you report percentages associated with a single variable’s (or crosstabular) categories, do not refer to a percentage found “in category one” or “in category two.” Since all categories of a variable (X or Y) must be properly labeled, report the percentages found across those labels (i.e., “55 percent have ‘A Great Deal’ of support for banks and financial institutions,” not “55 percent were found in category one”). Related to this, be sure to present each analysis of a dependent variable (Y) in its own paragraph. Do not present a one or two page-long run together paragraph that includes analyses of multiple dependent variables. This also includes separate paragraphs for each unique X’s impact on the same Y (i.e., X1 and X2 by Y1 should involve two separate paragraphs).
6. Finally, try to keep out any personal politics in your discussion and analysis. Future employers are interested solely in “just the facts” of an assignment you’re given – not your personal opinion. A few students decided to include their perceptions of affirmative action policy in their reports which, while interesting, have little to do with the way the data unfolded at this descriptive stage of the course.
I hope this helps!
Professor Ziner
1. For organizational purposes, in any univariate analysis section of a report, provide your descriptive analysis (means, standard deviations, percentage breakdowns, etc.) of the independent variables before you begin your singular analysis and discussion of the dependent variable(s).
2. When it comes to missing data (i.e., “refusals,” “don’t knows,” “no answers,” “not applicables,” etc.) associated with a univariate or bivariate analysis, unless you’re asked to do so, you need not report when one person or a non-trivial number of persons refuse to answer a survey item. By focusing on the VALID PERCENT column, with properly assigned missing cases, SPSS removes (excludes) those missing cases from the column for a “clean” interpretation of the results. In national surveys, such as those conducted by the National Opinion Research Center (NORC), people who do not respond to an item generally do not invalidate either the entire survey or any subset of variables analyzed within it.
3. Some students have incorrectly introduced the term “correlation” in our first BSF in the following way: “From the results, I cannot see any correlation between X and Y.” As we will soon discover in class, a correlation is a statistical measure of the strength of the relationship between at least an ordinal level X and Y and should only be used in that context. To use the term as a synonym for “relationship” or “association” would, therefore, be incorrect when conducting a crosstabular analysis.
4. The integration of tables and charts, while previously discussed in class and at this blog, needs additional clarification. Never place a table or chart in the center of your text discussion – only to the right (with discussion on the left) or, preferably, below the relevant discussion. Moreover, always label a table within its title (e.g., “TABLE 1C: Gender of MBA Students by Attitudes Toward Management Scores”) and reference the table/chart in your text as previously described (i.e., “See TABLE 1C”). Any unlabeled table or chart, whether referenced or not somewhere in your analysis, does not belong in the report.
5. When you report percentages associated with a single variable’s (or crosstabular) categories, do not refer to a percentage found “in category one” or “in category two.” Since all categories of a variable (X or Y) must be properly labeled, report the percentages found across those labels (i.e., “55 percent have ‘A Great Deal’ of support for banks and financial institutions,” not “55 percent were found in category one”). Related to this, be sure to present each analysis of a dependent variable (Y) in its own paragraph. Do not present a one or two page-long run together paragraph that includes analyses of multiple dependent variables. This also includes separate paragraphs for each unique X’s impact on the same Y (i.e., X1 and X2 by Y1 should involve two separate paragraphs).
6. Finally, try to keep out any personal politics in your discussion and analysis. Future employers are interested solely in “just the facts” of an assignment you’re given – not your personal opinion. A few students decided to include their perceptions of affirmative action policy in their reports which, while interesting, have little to do with the way the data unfolded at this descriptive stage of the course.
I hope this helps!
Professor Ziner
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