1. Give an appropriate descriptive summary, including
the shape, center, spread and outliers of the distribution, from a set of raw
data.
2. Analyze the relationship between two variables using the scatterplot, correlation
coefficient, and the least squares regression line.
3. Student will be able to use the normal distribution to find approximate solutions
to problems about sample means and sample proportions.
This course introduces data analysis. Topics include
design of experiments, descriptive statistics, correlation and regression, probability,
sampling, estimation, and significance testing. Students use appropriate technology
to analyze realworld data.
MATH 64 with a grade of “C” or better or qualification through the Math Competency Exam or approved equivalent.
week 1 lectures: 1/14
1/16 
week 9 lectures: 3/18 
week 2 lectures: 1/23 
week 10 lectures: 3/25 3/27 practice exam 2 
week 11 lectures: 4/3 

week 12 lectures: 4/10 

week 5 lectures: 2/11
prior exam 1 

week 6 lectures: 2/20 

week 15 lectures: 4/29


week 8 lectures: 3/4
3/6 discrete probability distribution worksheet 
week 16 lectures: 5/8 
Constructing a CI using the tdistribution
SYLLABUS
AND TENTATIVE SCHEDULE
MATH 103 GUIDED
NOTEBOOK
MATH 103 PROJECT INSTRUCTIONS
CENTRAL
LIMIT THEOREM ANIMATION
TI CALCULATOR
STEPBYSTEP TUTORIALS
Standard Normal Table
tdistributoion
Table
EXAM 2  
sample project 
CHAPTER 11 
