Learning Path 3 lecture: Collecting data using a Sample
I. Sampling
What is sampling?
A. An activity:
Question of interest: How much did students in this section of ST 351 spend on course materials this
quarter, on average? Collect data on 10 students to
Learning Path 12 lecture notes: Sampling Distributions
I.
What is a Sampling Distribution?
In general, a sampling distribution is a list of the sample statistics from samples of the
same sample size from a population.
A. Examples of Sampling Distributions
Learning Path 11 lecture notes: Type of Inference
As mentioned in the pre-lecture material, it is important to start feeling comfortable with recognizing when
a scenario involves inference and when it does not, and if it does involve inference, which type
Learning Path 13 lecture notes: Introduction to Confidence Intervals
I.
Quick review of pre-lecture material
An interval estimate is a range of values that we think will contain a population
parameter.
There will be a lower bound to this range of values
Learning Path 15 lecture notes: Constructing a Confidence Interval for a
Population Mean or Median using Bootstrap Methods
I.
Important ideas
We will have data from a sample
We want to use that data to make a generalization about the population from which
ST 351
Midterm Part I solutions
Fall 2013
Form 1
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b
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c
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ST 351
Midterm Part II
Short answer section 16 points
Fall 2014
PRINT NAME
Lab Day (circle):
Wednesday
Thursday
Lab Time (circle): 8AM 9:30 11:00 12:30 2:00 3:30 5:00 6:30 8PM
1.
February 12, 2009 marked the 200th anniversary of Charles Darwin's birth. To
ST 351
Midterm Part II
Short answer section 16 points
Fall 2014
PRINT NAME
Lab Day (circle):
Wednesday
Thursday
Lab Time (circle): 8AM 9:30 11:00 12:30 2:00 3:30 5:00 6:30 8PM
1.
th
February 12, 2009 marked the 200 anniversary of Charles Darwin's birth. T
ST 351
Lab Activity 1
Introduction to R
Objectives of this lab activity
Basic features of R and RStudio
Entering data into R
Calculating a mean, tabulating values of a categorical variable, and creating a bar chart
Introduction
R
R is a programming langua
Learning Path 6 lecture notes: Collecting data using Experiments
I. Illustrating important experimental design concepts through an activity
Return to the Sudoku experiment. The experiment will be performed in lecture and well use the data
collected in a l
Learning Path 10A lecture notes: What is Probability?
In the pre-lecture material, some terminology and the definition of probability were discussed. In lecture,
we will focus on estimating probabilities using simulation.
I. Why do we estimate probabiliti
Lesson 10B Lecture Notes: Probability Rules!
Motivation: In Lesson 10A, we discussed that probability is a long-run proportion. To determine the
probability of an outcome (or at least estimate it), a large number of trials had to be performed.
With the ai
Learning Path 9 Lecture notes: Finding Percentages The Uniform and Normal
Distributions
I.
Review of Pre-Lecture Material
A. Density Curves
The two properties of density curves:
There are two important characteristics of all density curves:
1) it is alway
Learning Path 8 lecture notes: Exploring Categorical Data
Investigating the relationship between two categorical variables
Lets continue discussing the example started in the pre-lecture material.
Example
The British Journal of Cancer reported a study on
Learning Path 4 lecture: Exploring a single quantitative variables of interest
I.
Comments on the shape, center, and spread of quantitative data
A.
Shape
1.
For each graph, state whether it is better to use it for smaller or larger sample sizes.
DOTPLOT
H
Learning Path 7 lecture notes: Exploring the relationship between a quantitative
response variable and a categorical explanatory variable
I.
Interpreting a Box-and-Whisker Plot
Return to the example from the Learning Path 7 pre-lecture material on the ave
Learning Path 2 lecture: The Research Question
I. Review of important definitions
Example 1:
Studies have recently investigated the effectiveness of aspirin to prevent certain types of cancer. In such
studies, patients have been observed as to whether or
Learning Path 5 lecture notes: Collecting data using Observational Studies
I. Association versus Causation
Example: Smoking and Lung Cancer Studies
In the mid-20th Century, many studies were performed to examine the association between smoking and
lung ca
Learning Path 14 lecture notes: Bootstrap Samples and the Bootstrap
Distribution of Sample Means
I.
Why we need a Bootstrap Distribution
As we learned in Learning Path 13, the standard deviation of the true sampling distribution is used
when constructing