IntroductionIn this article, we'll start to put things together by introducing an analysis plan and many other topics essential to understanding the data we've collected. We will construct dummy tables, interpret and present different variables.Analysis Plan SummaryTo start the analysis plan, this writer plans to start with a pre-analysis plan to ensure he is ready to take on the stain. Below is the checklist presented by David McKenzie (2012) that this author will follow.1. Description of the sample to be used in the study: In the author's situation, the sample consists of area residents who have dropped out of school and are aged 16 to 25 years. Key Data Sources: The key data source will be people who volunteer to respond to our survey.3. Hypotheses to be tested throughout the causal chain: The key hypothesis for this author is whether or not alternative teaching methods have an effect on reducing secondary school dropout rates.4. Specify how the variables will be constructed: This area will be where we record our data of specific variables that will be used, how non-existent variables will be handled, what operations will be used to take care of deviations.5. Specify the treatment effect equation to be estimated: This author, as an example, chose post-specification to use for this study. What controls will be included in the regression? For our study, it will be high schools and their students.6. What is the plan for handling multiple outcomes and multiple hypothesis testing? This study will combine various criteria into a single measurement scale in which several of the questions used together will help us understand the overall abilities to meet the needs of all students.7. ...... middle of document ......how we know if two variables are directly or closely correlated. Regression analysis will require a dummy weight to start with and will allow us to correctly weight each variable by telling us whether the weight we initially give is too high or too low. Multivariate analysis The use of multivariate statistics will allow the study of analyzable but complex data. datasets from a dataset. For this study, using multivariate analysis will not be particularly useful because the data does not become that complex. If it is used, it will be used more for hypothesis testing than for overall statistical use. For our statistical technique, we will use ANOVA which this author found to be the best. Works CitedMcKenzie, D. (2012, October 28). [Web log message]. Retrieved from http://blogs.worldbank.org/impactevaluations/a-pre-analysis-plan-checklist