## STAT 651 (Section 602: TR - 14:20-15:35, Blocker 113) Statistics in Research (Fall 2015)

Instructor: Suhasini Subba Rao (office: Blocker 432).

Statistical packages: You can use any, but I will be using JMP (a click version of SAS), which is available free to you.

I will post the lecture notes each week.

GRADES: I am still in the process of compiling the grades. Please DO NOT visit my office until I say the grades are out.

Midterm is on Tuesday 27th October.

Week 1:

Week 2:
Week 3:
Week 4:
Week 5:
• Lecture 11. See also Section 5.1 and 5.2 of Ott and Longnecker.

Here is a little maths help for the length of CIs intervals.

Very useful applet explaining that the sample mean has a distribution which is close to a normal distribution Sampling distribution In class I will be using a similar applet but in Statcrunch - it tends to be more versatile.

Handout on the central limit theorem CLT.

• Lecture 13

If you want to understand that an estimator being `close' to the mean implies that the variance is small, please take a look at variance and estimators.

Week 6:
Week 7: Week 8: Week 9:
• Midterm - Bring 3 sides of cheatsheet, calculator (of any type, but not phone - it cannot have wireless capability), normal and z-tables.
• Lecture 20
Week 10: Week 11: Week 12: Week 13:
• PROJECT (due 11th December, 2015, by 4pm). To be handed in the main statistics office or me in person (NOT the TA, I grade the projects!). You have a choice of:

• Up to three people are allowed in each group. However, if there are more than two people in a group, at least one must be from a different department (same college is fine).
• Lazy students may be tempted to copy previous years projects. I will be able to detect this - the numbers and results have changed. If you do so, you will get an immediate fail and will be reported to Aggie honour code.
Week 14: Week 15:

Homework (due 1st December - no extensions given). Solution

Homeworks (optional)

JMP Help

Past Midterm Exams:

Past Final Exams: