Psyc451 Project/Conference TimelineThe final products of the project will be either: 1) a poster & handout or 2) a PowerPoint presentation & handout.The conference this semester is at Washburn University in Topeka Kansas on March 18-19. Unfortunately this is the Friday and Saturday before Spring Break. I understand that many of you will not want to miss classes that Friday and/or you may have plans for that weekend, and I do not expect you to change those plans to attend this conference! There will be at least one other opportunity this semester to present your project.All of you will be completing the project on the same timeline, whether or not you intend to attend the conference There are several stages to the project, which are chosen to divide the process into smaller, more manageable steps. There will be a strictly enforced schedules and nasty penalties for turning things in late. Any assignment handed in lateon the day it is due will lose 2% from the final project grade. There is an additional 2% penalty for each additional day late the assignment is handed in. Points lost for handing in assignments late can not be “recovered” by rewriting the assignment. Only Cal (not your lab TA) can OK an assignment being late, and only if you talk to him before the assignment is late.Scope of the project:You may pick one of four types of analyses for your project or bargain with Cal for a more elaborate project:- Nested/non-nested regression model comparisons (6-10 predictors) -- using one criterion variable & one population - Comparing a full regression model (5-8 predictors) across populations/groups -- using one criterion variable.- Comparing a full regression model (5-8 predictors) across criterion variables – using one population- Nested/non-nested ldf model comparisons (6-10 predictors) using one criterion variable & one population- Up to 5% “bonus” is available for more elaborate analyses (look better at the conference and in your applications)Remember: A “good model” is one that allows you to tell a story about what predictors are and aren’t related to the criterion – you are not trying to dig up a model with all significant predictors. However, so you will have something to write about, if your model is not significant or has no significant predictors you should try other predictorsSubmission/Proposal Schedule – everybody follows this schedule, whether or not you plan to attend the conference.To Be Announced after collaboration with TAsProposal for 451 Laboratory Project Name1. What data set will you be using (it must be approved by Cal if it is not one of the Project Datasets)2. Circle the statistical model you plan to use multiple regression or linear discrininant function For multiple regression  what is your criterion variable? Mean = std = For linear discriminant function  what is your criterion variable?  tell the name and frequency of each condition3. Specify the criterion and predictor variable(s) – be sure to choose the correct type of analysis.Nested/non-nested model comparisons (6-10 predictors) -- using one criterion variable & one population Criterion variable Population1st model name variables2nd model name variablesWhy is it interesting to compare these models?Comparing a full model (5-8 predictors) across populations/groups -- using one criterion variable.Criterion variable1st population 2nd populationVariables Why is it interesting to compare these populations on this model?Comparing a full model (5-8 predictors) across criterion variables – using one population1st Criterion variable 2nd Criterion variablePredictorsPopulationWhy is it interesting to compare these criterion variables on this model? Something more interesting? If you plan to perform a combination of these, please specify what populations, criterion and models are involved and the comparisons you want to