ADMS 2320: TERM TEST #2 PREP · Fall 2024

CHAPTER LESSONS - FREE

Chapter 5: Data Collection And Sampling

5 Topics | 1 Quiz

Introduction to Data Collection and Sampling

Data Collection

Types of Samples

Types of Errors

Chapter 05 Quiz

Chapter 7.1: Random Variables and Discrete Probability Distributions

12 Topics | 1 Quiz

Discrete Variables vs. Continuous Variables

Relative Frequencies + Discrete Variables (Q1a)

Requirements for a Distribution of a Discrete Random Variable (Q1a)

Population Mean = Expected Value E(X) (Q1b)

Population Variance V(X) and Standard Deviation (Q1c-d)

Variance | The Shortcut Formula

Probability Trees and Discrete Variables (Q2a)

Discrete Probabilities (Q2b-c)

Expected Value (Q2d)

Variance of X (2e)

Laws of Expected Value (Q2f)

Probability Tree (Q3)

Chapter 07.1 Quiz

Chapter 8.1: Probability Density Functions

3 Topics

Probability Density Functions

Uniform Distributions

Uniform Distribution – Example

CHAPTER LESSONS - PREMIUM CONTENT

Chapter 7.4: Binomial Distribution

6 Topics | 1 Quiz

The Binomial Experiment

The Binomial Probability Distribution (The Formula)

Using Binomial Tables

10 | Binomial Probability

11 | More Binomial

12 | Even More Binomial

Chapter 07.4 Quiz

Chapter 8.2: Normal Distribution

4 Topics | 1 Quiz

Normal Distribution – Question #1 and #2

Normal Distribution – Question #3

Normal Distribution – Question #4

Normal Distribution – Question #5

Chapter 08 Quiz

Chapter 9: Sampling Distributions

6 Topics | 1 Quiz

Introduction to Sampling Distributions

1 | Distribution of One Sample Mean

2 | Comparing Chapters 9 and 8

3 | Probability of a Sample Mean

4 | Binomial vs Sample Proportions

Comparing Two Populations

Chapter 09 Quiz

Chapter 10: Introduction to Estimation

8 Topics | 1 Quiz

Introduction to Estimation

Point Estimators

Confidence Interval Estimate of the Mean (Q1)

Quick Reference Table

Interpreting Confidence Intervals (Q2a–b)

Confidence Interval Width vs. Confidence Level (Q2c–d)

Confidence Interval Width vs. Sample Size, Standard Deviation, and Mean (Q2e–i)

Sample Size Determination (Q3)

Chapter 10 Quiz

PAST TESTS + SOLUTIONS FREE

Term Test #2 – Fall 2022 – Sample

3 Topics

Q1a) Ch8: Normal Distribution: Convert x → z → area « FREE SAMPLE

Q1b) Ch8: Normal Distribution: Convert x → z → area « FREE SAMPLE

Unlock ALL Past Term Test 2’s

PAST TESTS + SOLUTIONS - PREMIUM CONTENT

Term Test #2 – Fall 2022

14 Topics

Q1a) Ch8: Normal Distribution: Convert x → z → area

Q1b) Ch8: Normal Distribution: Convert x → z → area

Q1c) Ch8: Uniform Distribution

Q1d) Ch8: Normal Distribution: Convert area → z → x

Q2a) Ch9: Normal Distribution: Convert x̄ → z → area

Q2b) Ch9: Normal Distribution: Convert p̂ → z → area

Q2c) Ch9: Normal Distribution: Convert (x̄1-x̄2) → z → area

Q2d) Ch10: Estimation: Interpretation

Q3a) Ch7.4: Binomial: Table

Q3b) Ch7.4: Binomial: Table

Q3c) Ch7.4: Binomial: Expected value, Binomial: Variance

Q3d) Ch7.4: Binomial: Laws of Variance

Q3e) Ch7.4: Binomial: Laws of Expected Value

Q3f) Ch7.4: Binomial: Formula

Term Test #2 – Winter 2021

12 Topics

Q1) Ch7.4: Binomial Setting

Q1a) Ch7.4: Binomial: Formula

Q1b) Ch7.4: Binomial: Mean, Binomial: Variance

Q1c) Ch7.4: Binomial: Table

Q1d) Ch7.4: Binomial: Table

Q2a) Ch8: Normal Distribution: Convert x → z → area

Q2b) Ch8: Normal Distribution: Convert area → z → x → μ

Q2c) Ch9: Normal Distribution: Convert p̂ → z → area

Q2d) Ch9: Normal Distribution: Convert (x̄1-x̄2) → z → area

Q3a)b) Ch8: Uniform Distribution

Q3c) Ch10: Estimation: Minimum Sample Size

Q3d) Ch10: Estimation: Bound on the Error

Term Test #2 – Winter 2018

12 Topics

Q1a) Ch8: Uniform Distribution

Q1b) Ch8: Uniform Distribution

Q1c) Ch8: Continuous Distribution: Theory

Q1d) Ch8: Uniform Distribution

Q1e) Ch7.4: Binomial: Table

Q1f) Ch7.4: Binomial: Table, Binomial: Formula

Q1g) Ch9: Normal Distribution: Convert p̂ → z → area

Q2a) Ch8: Normal Distribution: Convert x → z → area

Q2b) Ch9: Normal Distribution: Convert x̄ → z → area

Q2c) Ch8: Normal Distribution: Convert area → z → x

Q2d) Ch9: Normal Distribution: Convert (x̄1-x̄2) → z → area

Q2e) Ch8: Normal Distribution: Convert x → z → area, Binomial: Formula

Term Test #2 – Fall 2017

15 Topics

Q1) Setup: Ch7.4: Binomial: Identification

Q1a) Ch7.4: Binomial: Table

Q1b) Ch7.4: Binomial: Table

Q1c) Ch7.4: Binomial: Table

Q1d) Ch7.4: Binomial: Theory, Ch6 Probability

Q1e) Ch7.4: Binomial: Formula

Q1f) Ch7.4: Binomial: Expected Value

Q1g) Ch7.4: Binomial: Variance

Q1h) Ch7.4: Binomial: Formula

Q2a) Ch8: Normal Distribution: Convert x → z → area

Q2b) Ch9: Normal Distribution: Convert x̄ → z → area

Q2c) Ch8: Normal Distribution: Convert area → z → x

Q2d) Ch9: Normal Distribution: Convert (x̄1-x̄2) → z → area

Q2e) Ch7.4: Binomial: Formula

Term Test #2 – Fall 2016

14 Topics

Q1a) Ch7.4 Binomial: Mean

Q1b) Ch7.4 Binomial: Variance

Q1c) Ch4 Standard Deviation

Q1d) Ch7.4 Binomial: Formula

Q1e) Ch7.4 Binomial: Formula

Q1f) Ch7.4 Binomial: Formula

Q1g) Ch7.4 Binomial: Table

Q1h) Ch7.4 Binomial: Table

Q2a) Ch9: Central Limit Theorem

Q2b) Ch9: Variance of x̄

Q2c) Ch9 Normal Distribution: Convert x̄ → z → area

Q2d) Ch10 Confidence Interval Estimate of x̄

Q2e) Ch10 Estimation: Minimum Sample Size

Term Test #2 – Archive | Extra Chapter #7 Questions

5 Topics

Exam A – Binomial – 5 Questions

Exam B – Binomial – 4 Questions

Exam C – Random Variables and Probability Distributions – 4 Questions

Exam D – Binomial – 4 Questions

Exam E – Binomial – 5 Questions

Term Test #2 – Archive | Extra Chapter #8 Questions

4 Topics

Exam G – Normal Distribution – 4 Questions

Exam H – Normal Distribution – 3 Questions

Exam I – Normal Distribution – 1 Question

Exam J – Normal Distribution, Ch.9 Sampling Distribution of the Mean – 4 Questions

Term Test #2 – Archive | Extra Chapter #9 Questions

3 Topics

Exam K – Sampling Distribution of the Mean – 4 Questions

Exam L – Central Limit Theorem – 1 Question

Exam M – Sampling Distribution of a Proportion – 5 Questions

Point Estimators

ADMS 2320: TERM TEST #2 PREP · Fall 2024 Chapter 10: Introduction to Estimation Point Estimators

Using the sample mean to estimate the population mean may seem obvious, but a good estimator for a population parameter must have certain characteristics to be dependable. In this video I discuss the qualities of a good estimator: unbiasedness, consistency, and relative efficiency.

Test your understanding:

Time limit: 0

Quiz Summary

0 of 5 Questions completed

Questions:

Information

You have already completed the quiz before. Hence you can not start it again.

Quiz is loading…

You must sign in or sign up to start the quiz.

You must first complete the following:

Results

Quiz complete. Results are being recorded.

Results

0 of 5 Questions answered correctly

Time has elapsed

Average score
Your score

Categories

Not categorized 0%

1
2
3
4
5

Current
Review
Answered
Correct
Incorrect

Question 1 of 5

1. Question
A point estimator is defined as:
- a range of values that estimates an unknown population parameter.
- a range of values that estimates an unknown sample statistic.
- a single value that estimates an unknown population parameter.
- a single value that estimates an unknown sample statistic.
Correct

Incorrect
Question 2 of 5

2. Question
The problem with relying on a point estimate of a population parameter is that:
- it is virtually certain to be wrong.
- it doesn't have the capacity to reflect the effects of larger sample sizes.
- it doesn't tell us how close or far the point estimate might be from the parameter.
- All of these choices are true.
Correct

Incorrect
Question 3 of 5

3. Question
What does it mean for a point estimator to be unbiased?
- a) It always overestimates the population parameter.
- b) It always underestimates the population parameter.
- c) It overestimates and underestimates the population parameter equally.
- d) It always accurately estimates the population parameter.
Correct

Incorrect
Question 4 of 5

4. Question
What does it mean for a point estimate to be consistent?
- a) The point estimator is always correct.
- b) The point estimator becomes more accurate as the sample size increases.
- c) The point estimator becomes less accurate as the sample size increases.
- d) The point estimator remains the same regardless of the sample size.
Correct

Incorrect
Question 5 of 5

5. Question
What is relative efficiency in the context of point estimation?
- a) The point estimator is always efficient.
- b) The point estimator is chosen based on the lowest variation.
- c) The point estimator is chosen based on the highest variation.
- d) The point estimator is chosen based on the sample size.
Correct

Incorrect

Chapter 10 Questions PDF

Login

Accessing this chapter requires a login. Please enter your credentials below!

Username or Email Address

Password

Remember Me

Lost Your Password?