Reference no: EM133726393

The standard research report has the following elements, in this order:

A title that is informative and not sensational, emotional, or lyrical - you are not writing clickbait but rather telling your readers about the overall research question and the major findings. On the title page you must also include the names of all the group members, in alphabetical order.

An abstract (which is usually written as the last step and inserted immediately after the title) that
summarizes the research question, methods, and samples, and major findings.

An introduction that states the overall research question and the major hypotheses, accompanied by a discussion that contextualizes your research on the basis of what is believed about the relationship(s) between the variable(s) you are investigating.
A literature review ("Lit Review") that summarizes key previous research designs and findings, provides an overview of the existing field or subfield, and helps to motivate your research question and hypotheses (which might seek to replicate, challenge, or extend findings in the field). Hypotheses should phrased to be falsifiable and, if variables in the research are at ordinal level of measurement or above, the expected direction of the relationship should be specified.

A methods section of the report that discusses the overall design, the conceptual and operational definition of key variables and the choices of data analysis techniques should be described. In this course, information about the sampling, data collection, recording and coding, can be provided according to the documentation for the data set you are analyzing.

A results or findings section that presents what you found, both specific and more broadly
contextualized (see below).

A discussion or conclusions section in which you discuss and assess the results and findings,
outline any questions that arise from them, and possibly include specific ideas for social change and/or public policies.
A section entitled Works Cited or References in which you list all the sources you have referred to in your report.

More information about how to organize the section entitled Results or Findings, follows. To keep it simple, the suggestions are organized as guidelines or a check list for you to follow as you write the report.

One: Remind the reader of your overall research question and the specific hypotheses that you are testing.

Two: Write in the past tense.

Three: Restate each hypothesis, and then provide the following information for each.

Report the sample size for the specific test; if there are many missing values for the specific
test, write a brief discussion of that to account for listwise or pairwise exclusion of missing data.

Provide a table of descriptives for each variable in the specific hypothesis test; for numerical variables, this would probably include the mean, SD (standard deviation), SE (standard error), and perhaps the median and maximum and minimum. (In some research reports, the descriptive table could go at the start of the results section for all the variables in the hypotheses and does not have to be repeated.)

Briefly explain your choice of data analysis technique; then provide the value of the test statistic (e.g.,
t, F, chi-square), with its degrees of freedom if relevant.

Show the actual p-value found in the charts, or indicate whether p < .05, .01, etc. Or use a star code with * (meaning .05 level), ** (meaning .01 level), etc. As a matter of good form, mention your alpha level. Make clear whether or not the result was statistically significant.

Provide a measure of strength of the relationship: e.g., r, R-squared, or one or more measures of association for crosstabs with categorical variables.

Discuss and interpret this result in words, and provide a brief statement of it that would make sense to the nonexpert.

Four: Make sure to include the explanations required by the various types of data analysis you have used. Much of this is going to be automatically in the output for the question or hypothesis, so it is mostly a matter of importing this output into your research report and focusing on a good interpretation and discussion of it. Here are reminders about what to include with each type of data analysis technique.

Bivariate regression model: The software will provide results that include the coefficients for each independent variable in the model with p-values and/or stars to indicate whether it
is significant or not. It will also show R-squared, with an ANOVA to test its significance. Remember it might be rather weak, yet significant.

Bivariate scatter plots and regression lines:
Make sure that the independent variable is on the X-axis and the dependent variable
is on the Y-axis.
Try to get the equation and R-squared on the graph.
It is nice to label cases, especially cases that are decidedly "off the regression line:'

Multivariate models (multiple regression): Typically, the software will create a table in which the coefficients for each variable in the model are shown, with stars to indicate significant ones, and the adjusted R-squared for the model is provided. Several models utilizing different combinations of the variables in the study are often compared in a single table. All the variables in all the models are listed in a vertical column at the left side of the table. Then each model is placed in its own vertical column with the coefficient for the corresponding variable placed in the table and starred if it is significant. At the bottom of the column for each model, we can see its adjusted R-squared.

In a multiple regression, the coefficients are basically meaningless and what matters is if they are significant or not, as well as the value of the adjusted R-squared.

ANOVA: Be sure to obtain the descriptives so that the reader can see the dependent-variable means for the different groups or factors. (The means must be requested as an option in SPSS.) If you have three or more groups or factors, you should also obtain and report the results from a post-hoc test.