Score received: 100%
Disclaimer: I took great care and effort into writing each and every essay I have ever
submitted for this class. I expect you to do the same. I have uploaded these essays and
will continue to do so for the purposed of providing an exa
SOLUTIONS
STAT 1430 Recitation 6A Simpsons Paradox and Probability Rules
Mike and Tom are on a baseball team. They keep track of their batting statistics
for two seasons. They count the number of times they got a hit, and the number of
times they were at
Mount Hood Community College
MTH 243 Probability and Statistics I
Cassie Williams
Summer 2016
Graded Problem Set 4
Please use a different color, such as blue, in the text of your responses.
1. 1. Womens Heights
Assume that Womens heights are normally dist
Find the indicated confidence interval. Assume the standard error comes from a bootstrap distribution that is approximately normally distributed.
A 95% condence interval for a mean P If the sample has n = 60 with 7 = 63 and 5 = 13 , and the standard error
Mount Hood Community College
MTH 243 Probability and Statistics I
Cassie Williams
Summer 2016
Graded Problem Set 2
Please use a different color, such as blue, in the text of your responses.
Life Expectancy Part 2 Refer to the Data Set All Countries. (Data
Announcements
Turn your clicker to channel 7
Chapter 8-9 online Canvas Quiz due tonight
Chapter 9 written assignment due this week in recitation
Classic Probability Rules
Probability Terminology
Trial - A single attempt at a probability experiment
Exa
Announcements
Turn your clicker to channel 7
Starting Probability today
Chapter 8-9 quiz due Monday
Other types of experimental designs:
Block Design: Matched pairs
A matched-pairs design is a randomized blocked experiment in which
each block consists
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ModelYear MfrName
2017 aston martin
2017 aston martin
2017 aston martin
2017 aston martin
2017 BMW
2017 BMW
2017 BMW
2017 BMW
2017 BMW
2017 BMW
2017 BMW
2017 BMW
2017 BMW
2017 BMW
2017 BMW
2017 BMW
2017 BMW
2017 BM
Data Analysis #3
ST314
Total: 40 points
Due: Monday October 31st, at 11:59pm PST
Material from Week 4 and 5 Course Notes and Chapter 5, 6, 7, and 8 are covered on this
analysis.
R code and Datasets can be found in the Data Analysis #3 Instructions
Please
Data Analysis #1
ST314
Total: 40 points
Due: Monday October 3rd at 11:59pm PST
Please Download, complete and upload as PDF or Word Document in Canvas by the due
date.
No other format will be accepted. Typing or entering answers by hand is accepted as
long
Data Analysis #2
ST314D
Total: 40 points
Due: Monday October 17th at 11:59pm PST
Please Download, complete and upload as PDF or Word Document in Canvas by the due date.
No other format will be accepted. Typing or entering answers by hand is accepted as lo
Statistics Assignment II
Part 1
1)
2) Frequency Table
Choice
Frequency
Percentage
Scissors
Rock
Paper
895
736
677
38.8%
31.9%
29.3%
3) Both the bar plot and frequency table reveal the same result. They both suggest that students in Stats
351 show a slight
Stats Assignment One
Part One
1)
2)
a) The Sample Means distribution is near symmetrical yet is slightly right skewed. Given its
near symmetry the proper measure of center is the mean.
b) The mean distribution of the sample means is 5.503.
Self-selecting
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
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
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
d
a
c
b
e
b
e
c
c
b
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
b
a
d
a
c
a
b
c
c
d
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
c
d
a
e
a
b
e
b
a
a
31.
32.
33.
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35.
36.
37.
38.
39.
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