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This document provides instructions for students to classify their own fingerprints into three patterns - arches, loops, and whorls. Students are asked to count the number of each pattern in their own fingerprints and record the totals. They then tally the class totals for each pattern and compare them to expected averages. Finally, students separate the class totals by sex and identify the most common patterns for males and females, comparing those averages to expectations as well.
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Grouped Mean Median Mode
Mean Median Mode for Grouped Data containing Class Intervals and Bins in Statistics
35881 DiscussionNumber of Pages 1 (Double Spaced)Number o.docx
35881 Discussion
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Type of document: Essay
Academic Level:Master
Category: Psychology
Language Style: English (U.S.)
Order Instructions: Attached
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35876 Topic: Discussion3
Number of Pages: 1 (Double Spaced)
Number of sources: 1
Writing Style: APA
Type of document: Essay
Academic Level:Master
Category: Psychology
Language Style: English (U.S.)
Order Instructions: Attached
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Discussion: Please discuss, elaborate and give example on the topic. Be careful with grammar and spelling. No running head please. Please Use only the reference I will attach as the professor will not be able to give grade.
Author: (Jackson, S. L. (2017). Statistics plain and simple. (4th ed.). Boston, MA: Cengage Learning.)
Topic
What level of measurement can be used for this test for the independent and dependent variables?
Reference:
Module 9: The Single-Sample z Test
The z Test: What It Is and What It Does
The Sampling Distribution
The Standard Error of the Mean
Calculations for the One-Tailed z Test
Interpreting the One-Tailed z Test
Calculations for the Two-Tailed z Test
Interpreting the Two-Tailed z Test
Statistical Power
Assumptions and Appropriate Use of the z Test
Confidence Intervals Based on the z Distribution
Review of Key Terms
Module Exercises
Critical Thinking Check Answers
Module 10: The Single-Sample t Test
The t Test: What It Is and What It Does
Student's t Distribution
Calculations for the One-Tailed t Test
The Estimated Standard Error of the Mean
Interpreting the One-Tailed t Test
Calculations for the Two-Tailed t Test
Interpreting the Two-Tailed t Test
Assumptions and Appropriate Use of the Single-Sample t Test
Confidence Intervals Based on the t Distribution
Review of Key Terms
Module Exercises
Critical Thinking Check Answers
Chapter 5 Summary and Review
Chapter 5 Statistical Software Resources
In this chapter, we continue our discussion of inferential statistics—procedures for drawing conclusions about a population based on data collected from a sample. We will address two different statistical tests: the z test and t test. After reading this chapter, engaging in the Critical Thinking checks, and working through the problems at the end of each module and at the end of the chapter, you should understand the differences between the two tests covered in this chapter, when to use each test, how to use each to test a hypothesis, and the assumptions of each test.
MODULE 9
The Single-Sample z Test
Learning Objectives
•Explain what a z test is and what it does.
•Calculate a z test.
•Explain what statistical power is and how to make statistical tests more powerful.
•List the assumptions of the z test.
•Calculate confidence intervals using the z distribution.
The z Test: What It Is and What It Does
The z test is a parametric statistical te.
35880 Topic Discussion7Number of Pages 1 (Double Spaced).docx
35880 Topic: Discussion7
Number of Pages: 1 (Double Spaced)
Number of sources: 1
Writing Style: APA
Type of document: Essay
Academic Level:Master
Category: Psychology
Language Style: English (U.S.)
Order Instructions: Attached
I will attach the instruction
Please follow them carefully
Discussion3: Please discuss, elaborate and give example on the topic below. Please use only the reference I attach. Please be careful with grammar and spelling. No running head please.
Author: Jackson, S.L. (2017). Statistics Plain and Simple (4th ed.): Cengage Learning
Topic:
You find out that the average 10th grade math score, for Section 6 of the local high school, is 87 for the 25 students in the class. The average test score for all 10th grade math students across the state is 85 for 1,800 students. The standard deviation for the state is 3.8.
Answer the following questions:
· What z score do you calculate?
· What is the area between the mean and the z score found in Appendix A of the textbook?
· What does this mean about the probability of this test score difference occurring by chance? Is it
less than 0.05?
Reference
Module 9: The Single-Sample z Test
The z Test: What It Is and What It Does
The Sampling Distribution
The Standard Error of the Mean
Calculations for the One-Tailed z Test
Interpreting the One-Tailed z Test
Calculations for the Two-Tailed z Test
Interpreting the Two-Tailed z Test
Statistical Power
Assumptions and Appropriate Use of the z Test
Confidence Intervals Based on the z Distribution
Review of Key Terms
Module Exercises
Critical Thinking Check Answers
Module 10: The Single-Sample t Test
The t Test: What It Is and What It Does
Student's t Distribution
Calculations for the One-Tailed t Test
The Estimated Standard Error of the Mean
Interpreting the One-Tailed t Test
Calculations for the Two-Tailed t Test
Interpreting the Two-Tailed t Test
Assumptions and Appropriate Use of the Single-Sample t Test
Confidence Intervals Based on the t Distribution
Review of Key Terms
Module Exercises
Critical Thinking Check Answers
Chapter 5 Summary and Review
Chapter 5 Statistical Software Resources
In this chapter, we continue our discussion of inferential statistics—procedures for drawing conclusions about a population based on data collected from a sample. We will address two different statistical tests: the z test and t test. After reading this chapter, engaging in the Critical Thinking checks, and working through the problems at the end of each module and at the end of the chapter, you should understand the differences between the two tests covered in this chapter, when to use each test, how to use each to test a hypothesis, and the assumptions of each test.
MODULE 9
The Single-Sample z Test
Learning Objectives
•Explain what a z test is and what it does.
•Calculate a z test.
•Explain what statistical power is and how to make statistical tests more powerful.
•List the assumptions of the z test.
•Calculate confidence intervals usi.
35878 Topic Discussion5Number of Pages 1 (Double Spaced).docx
35878 Topic: Discussion5
Number of Pages: 1 (Double Spaced)
Number of sources: 1
Writing Style: APA
Type of document: Essay
Academic Level:Master
Category: Psychology
Language Style: English (U.S.)
Order Instructions: Attached
I will attach the instruction
Please follow them carefully
General Business Page 9
Unit 4
Due Wed 12/12
800-1,000 words / these will be turned into slides and added to your key assignment.
Study the following document: Methods for Managing Differences. Assume this communication strategy has been recommended by your employer for mediation when working with potential and existing business clients and partners.
Consider that there are basically two distinct types of cultures. One type is more cooperative, and the other is more competitive. It has been discovered that there are some conflicts occurring between some of the key players who need to come to agreement on specific critical areas of the deal for it to move forward. The top management would really like this deal to happen.
Imagine being in this situation, and create the scenario as you go through the process using the methods approach from above.
· Describe the steps you would take and any considerations along the way.
· How would you use the recommended method when working with individuals who exhibit a generally competitive culture?
· How would you use the recommended method when working with individuals who exhibit a generally cooperative culture?
· Would this cultural factor change the way you apply this method for managing differences? Why or why not? Explain.
Create Section 4 of your Key Assignment presentation: Global Negotiations. Refer to Unit 1 Discussion Board 2 for a description of this section. Submit a draft of your entire presentation for your instructor to review.
Discussion 2: Discuss, elaborate and give example on the topic below. Please use only the reference I attach. Please be careful with grammar and spelling. No running head Please.
Author: Jackson, S.L. (2017). Statistics Plain and Simple (4th ed.): Cengage Learning
Topic
Review this week’s course materials and learning activities, and reflect on your learning so far this week. Respond to one or more of the following prompts in one to two paragraphs:
1. Provide citation and reference to the material(s) you discuss. Describe what you found interesting regarding this topic, and why.
2. Describe how you will apply that learning in your daily life, including your work life.
3. Describe what may be unclear to you, and what you would like to learn.
Reference:
Module 9: The Single-Sample z Test
The z Test: What It Is and What It Does
The Sampling Distribution
The Standard Error of the Mean
Calculations for the One-Tailed z Test
Interpreting the One-Tailed z Test
Calculations for the Two-Tailed z Test
Interpreting the Two-Tailed z Test
Statistical Power
Assumptions and Appropriate Use of the z Test
Confidence Intervals Based on the z Distribution
Review of Key Term.
Recommended
Grouped Mean Median Mode
Mean Median Mode for Grouped Data containing Class Intervals and Bins in Statistics
35881 DiscussionNumber of Pages 1 (Double Spaced)Number o.docx
35881 Discussion
Number of Pages: 1 (Double Spaced)
Number of sources: 1
Writing Style: APA
Type of document: Essay
Academic Level:Master
Category: Psychology
Language Style: English (U.S.)
Order Instructions: Attached
I will attach the instruction
Please follow them carefully
35876 Topic: Discussion3
Number of Pages: 1 (Double Spaced)
Number of sources: 1
Writing Style: APA
Type of document: Essay
Academic Level:Master
Category: Psychology
Language Style: English (U.S.)
Order Instructions: Attached
I will attach the instruction
Please follow them carefully
Discussion: Please discuss, elaborate and give example on the topic. Be careful with grammar and spelling. No running head please. Please Use only the reference I will attach as the professor will not be able to give grade.
Author: (Jackson, S. L. (2017). Statistics plain and simple. (4th ed.). Boston, MA: Cengage Learning.)
Topic
What level of measurement can be used for this test for the independent and dependent variables?
Reference:
Module 9: The Single-Sample z Test
The z Test: What It Is and What It Does
The Sampling Distribution
The Standard Error of the Mean
Calculations for the One-Tailed z Test
Interpreting the One-Tailed z Test
Calculations for the Two-Tailed z Test
Interpreting the Two-Tailed z Test
Statistical Power
Assumptions and Appropriate Use of the z Test
Confidence Intervals Based on the z Distribution
Review of Key Terms
Module Exercises
Critical Thinking Check Answers
Module 10: The Single-Sample t Test
The t Test: What It Is and What It Does
Student's t Distribution
Calculations for the One-Tailed t Test
The Estimated Standard Error of the Mean
Interpreting the One-Tailed t Test
Calculations for the Two-Tailed t Test
Interpreting the Two-Tailed t Test
Assumptions and Appropriate Use of the Single-Sample t Test
Confidence Intervals Based on the t Distribution
Review of Key Terms
Module Exercises
Critical Thinking Check Answers
Chapter 5 Summary and Review
Chapter 5 Statistical Software Resources
In this chapter, we continue our discussion of inferential statistics—procedures for drawing conclusions about a population based on data collected from a sample. We will address two different statistical tests: the z test and t test. After reading this chapter, engaging in the Critical Thinking checks, and working through the problems at the end of each module and at the end of the chapter, you should understand the differences between the two tests covered in this chapter, when to use each test, how to use each to test a hypothesis, and the assumptions of each test.
MODULE 9
The Single-Sample z Test
Learning Objectives
•Explain what a z test is and what it does.
•Calculate a z test.
•Explain what statistical power is and how to make statistical tests more powerful.
•List the assumptions of the z test.
•Calculate confidence intervals using the z distribution.
The z Test: What It Is and What It Does
The z test is a parametric statistical te.
35880 Topic Discussion7Number of Pages 1 (Double Spaced).docx
35880 Topic: Discussion7
Number of Pages: 1 (Double Spaced)
Number of sources: 1
Writing Style: APA
Type of document: Essay
Academic Level:Master
Category: Psychology
Language Style: English (U.S.)
Order Instructions: Attached
I will attach the instruction
Please follow them carefully
Discussion3: Please discuss, elaborate and give example on the topic below. Please use only the reference I attach. Please be careful with grammar and spelling. No running head please.
Author: Jackson, S.L. (2017). Statistics Plain and Simple (4th ed.): Cengage Learning
Topic:
You find out that the average 10th grade math score, for Section 6 of the local high school, is 87 for the 25 students in the class. The average test score for all 10th grade math students across the state is 85 for 1,800 students. The standard deviation for the state is 3.8.
Answer the following questions:
· What z score do you calculate?
· What is the area between the mean and the z score found in Appendix A of the textbook?
· What does this mean about the probability of this test score difference occurring by chance? Is it
less than 0.05?
Reference
Module 9: The Single-Sample z Test
The z Test: What It Is and What It Does
The Sampling Distribution
The Standard Error of the Mean
Calculations for the One-Tailed z Test
Interpreting the One-Tailed z Test
Calculations for the Two-Tailed z Test
Interpreting the Two-Tailed z Test
Statistical Power
Assumptions and Appropriate Use of the z Test
Confidence Intervals Based on the z Distribution
Review of Key Terms
Module Exercises
Critical Thinking Check Answers
Module 10: The Single-Sample t Test
The t Test: What It Is and What It Does
Student's t Distribution
Calculations for the One-Tailed t Test
The Estimated Standard Error of the Mean
Interpreting the One-Tailed t Test
Calculations for the Two-Tailed t Test
Interpreting the Two-Tailed t Test
Assumptions and Appropriate Use of the Single-Sample t Test
Confidence Intervals Based on the t Distribution
Review of Key Terms
Module Exercises
Critical Thinking Check Answers
Chapter 5 Summary and Review
Chapter 5 Statistical Software Resources
In this chapter, we continue our discussion of inferential statistics—procedures for drawing conclusions about a population based on data collected from a sample. We will address two different statistical tests: the z test and t test. After reading this chapter, engaging in the Critical Thinking checks, and working through the problems at the end of each module and at the end of the chapter, you should understand the differences between the two tests covered in this chapter, when to use each test, how to use each to test a hypothesis, and the assumptions of each test.
MODULE 9
The Single-Sample z Test
Learning Objectives
•Explain what a z test is and what it does.
•Calculate a z test.
•Explain what statistical power is and how to make statistical tests more powerful.
•List the assumptions of the z test.
•Calculate confidence intervals usi.
35878 Topic Discussion5Number of Pages 1 (Double Spaced).docx
35878 Topic: Discussion5
Number of Pages: 1 (Double Spaced)
Number of sources: 1
Writing Style: APA
Type of document: Essay
Academic Level:Master
Category: Psychology
Language Style: English (U.S.)
Order Instructions: Attached
I will attach the instruction
Please follow them carefully
General Business Page 9
Unit 4
Due Wed 12/12
800-1,000 words / these will be turned into slides and added to your key assignment.
Study the following document: Methods for Managing Differences. Assume this communication strategy has been recommended by your employer for mediation when working with potential and existing business clients and partners.
Consider that there are basically two distinct types of cultures. One type is more cooperative, and the other is more competitive. It has been discovered that there are some conflicts occurring between some of the key players who need to come to agreement on specific critical areas of the deal for it to move forward. The top management would really like this deal to happen.
Imagine being in this situation, and create the scenario as you go through the process using the methods approach from above.
· Describe the steps you would take and any considerations along the way.
· How would you use the recommended method when working with individuals who exhibit a generally competitive culture?
· How would you use the recommended method when working with individuals who exhibit a generally cooperative culture?
· Would this cultural factor change the way you apply this method for managing differences? Why or why not? Explain.
Create Section 4 of your Key Assignment presentation: Global Negotiations. Refer to Unit 1 Discussion Board 2 for a description of this section. Submit a draft of your entire presentation for your instructor to review.
Discussion 2: Discuss, elaborate and give example on the topic below. Please use only the reference I attach. Please be careful with grammar and spelling. No running head Please.
Author: Jackson, S.L. (2017). Statistics Plain and Simple (4th ed.): Cengage Learning
Topic
Review this week’s course materials and learning activities, and reflect on your learning so far this week. Respond to one or more of the following prompts in one to two paragraphs:
1. Provide citation and reference to the material(s) you discuss. Describe what you found interesting regarding this topic, and why.
2. Describe how you will apply that learning in your daily life, including your work life.
3. Describe what may be unclear to you, and what you would like to learn.
Reference:
Module 9: The Single-Sample z Test
The z Test: What It Is and What It Does
The Sampling Distribution
The Standard Error of the Mean
Calculations for the One-Tailed z Test
Interpreting the One-Tailed z Test
Calculations for the Two-Tailed z Test
Interpreting the Two-Tailed z Test
Statistical Power
Assumptions and Appropriate Use of the z Test
Confidence Intervals Based on the z Distribution
Review of Key Term.
Populations LabLAB #3, PART I ESTIMATING POPULATION SIZEO.docx
Populations Lab
LAB #3, PART I: ESTIMATING POPULATION SIZE
OBJECTIVE: To estimate population sizes and dynamics, you will be able to:
1. Compare and contrast methods of estimating population size (CLO #1)
2. Explain and use simple mathematical models of population dynamics (CLO #2)
3. Synthesize your research with the primary literature in ecology (CLO #3)
BACKGROUND INFORMATION:
Estimating the size of populations of organisms is a central problem in field ecology. It is one of the most basic pieces of information we can collect and is an important start for other ecological studies and conservation and management efforts. There are several ways to evaluate organism count (pop. size) or density (count/area), which are two means of characterizing populations
Sometimes, it is sufficient to evaluate organism relative abundance (relative representation of a species in a particular location). In that case, an ecologist can use indices. Indices are anything that can be correlated to the number of organisms in a given habitat (e. g., feces pellets, browsed branches, tracks, plant cover, etc.).
When population size is necessary, population estimates can be developed with a number of sampling and mathematical methods. Since it is rarely feasible to count an entire population, ecologists count a portion of the population and then estimate the total population size using mathematical functions. This can be done a number of ways, but in this exercise we will use two of the most common: density methods and mark-recapture methods.
Density method: In this method, ecologists will count the number of individuals in a prescribed area and then scale this measurement up to estimate the whole population size. Transect methods, in which an ecologist traverses a transect and counts individuals at specific locations along the line, are commonly used for plants and occasionally for animals.
Density methods require a few key assumptions:
1. The population is confined to a specific area
2. Individuals are readily detectable
3. Count areas are extensive relative to area occupied by population
Using these assumptions, ecologists use various models to calculate population size. In this lab, you will use a simple Seber (1973) model:
where N = the population estimate, N0 = the average number of organisms found in a plot. And p = the ratio of the individual plot area to total area (e.g. 25 cm2/820 cm2). Once you have calculated No, use the equation above to calculate N.
Confidence intervals provide a measure of the precision of our estimate (population size, N, in this case). A 95% confidence interval is a range of values that is thought to contain the true population size 95% of the time…that is, if you repeat your sampling and confidence interval calculation 100 times, the confidence intervals will capture the true value 95 of those times. To calculate the 95% confidence interval we can simply calculate the upper and lower confidence limits for N0 and then .
4 Solutions To Exercises 4.1 About These Solutions 4.2 Using The Table Of Ran...
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250 words, no more than 500· Focus on what you learned that made.docx
250 words, no more than 500
· Focus on what you learned that made an impression, what may have surprised you, and what you found particularly beneficial and why. Specifically:
· What did you find that was really useful, or that challenged your thinking?
· What are you still mulling over?
· Was there anything that you may take back to your classroom?
· Is there anything you would like to have clarified?
Your Weekly Reflection will be graded on the following criteria for a total of 5 points:
· Reflection is written in a clear and concise manner, making meaningful connections to the investigations & objectives of the week.
· Reflection demonstrates the ability to push beyond the scope of the course, connecting to prior learning or experiences, questioning personal preconceptions or assumptions, and/or defining new modes of thinking.
BELOW ARE LESSON COVERED
· This week's investigations introduce and explore one of the most common distributions (one you may be familiar with): the Normal Distribution. In our explorations of the distribution and its associated curve, we will revisit the question of "What is typical?" and look at the likelihood (probability) that certain observations would occur in a given population with a variable that is normally distributed. We will apply our work with Normal Distributions to briefly explore some big concepts of inferential statistics, including the Central Limit Theorem and Hypothesis Testing. There are a lot of new ideas in this week’s work. This week is more exploratory in nature.
Goals:
· Explore the Empirical Rule
· Become familiar with the normal curve as a mathematical model, its applications and limitations
· Calculate z-scores & explain what they mean
· Use technology to calculate normal probabilities
· Determine the statistical significance of an observed difference in two means
· Use technology to perform a hypothesis test comparing means (z-test) and interpret its meaning
· Use technology to perform a hypothesis test comparing means (t-test) (optional)
· Gather data for Comparative Study Final Project.
·
DoW #5: The SAT & The ACT
Two Common Tests for college admission are the SAT (Scholastic Aptitude Test) and the ACT (American College Test). The scores for these tests are scaled so that they follow a normal distribution.
· The SAT reported that its scores were normally distributed with a mean μ=896 and a standard deviation σ=174
· The ACT reported that its scores were normally distributed with a mean μ=20.6 and a standard deviation σ=5.2.
We have two questions to consider for this week’s DoW:
2. A high school student Bobby takes both of these tests. On the SAT, he achieves a score of 1080. On the ACT, he achieves a score of 30. He cannot decide which score is the better one to send with his college applications.
. Question: Which test score is the stronger score to send to his colleges?
· A hypothetical group called SAT Prep claims that students who take their SAT Preparatory course score higher o.
Applied Math 40S March 17, 2008
Working with grouped data, 1-variable statistics, and the standard deviation.
Applied 40S April 7, 2009
Introduction to the 3 different "meanings" of "area under the normal curve" and the ShadeNorm() command on the TI graphing calculators.
Module Five Normal Distributions & Hypothesis TestingTop of F.docx
Module Five: Normal Distributions & Hypothesis Testing
Top of Form
Bottom of Form
·
Introduction & Goals
This week's investigations introduce and explore one of the most common distributions (one you may be familiar with): the Normal Distribution. In our explorations of the distribution and its associated curve, we will revisit the question of "What is typical?" and look at the likelihood (probability) that certain observations would occur in a given population with a variable that is normally distributed. We will apply our work with Normal Distributions to briefly explore some big concepts of inferential statistics, including the Central Limit Theorem and Hypothesis Testing. There are a lot of new ideas in this week’s work. This week is more exploratory in nature.
Goals:
· Explore the Empirical Rule
· Become familiar with the normal curve as a mathematical model, its applications and limitations
· Calculate z-scores & explain what they mean
· Use technology to calculate normal probabilities
· Determine the statistical significance of an observed difference in two means
· Use technology to perform a hypothesis test comparing means (z-test) and interpret its meaning
· Use technology to perform a hypothesis test comparing means (t-test) (optional)
· Gather data for Comparative Study Final Project.
·
DoW #5: The SAT & The ACT
Two Common Tests for college admission are the SAT (Scholastic Aptitude Test) and the ACT (American College Test). The scores for these tests are scaled so that they follow a normal distribution.
· The SAT reported that its scores were normally distributed with a mean μ=896 and a standard deviation σ=174
· The ACT reported that its scores were normally distributed with a mean μ=20.6 and a standard deviation σ=5.2.
We have two questions to consider for this week’s DoW:
2. A high school student Bobby takes both of these tests. On the SAT, he achieves a score of 1080. On the ACT, he achieves a score of 30. He cannot decide which score is the better one to send with his college applications.
. Question: Which test score is the stronger score to send to his colleges?
· A hypothetical group called SAT Prep claims that students who take their SAT Preparatory course score higher on the SAT than the general population. To support their claim, they site a study in which a random sample of 50 SAT Prep students had a mean SAT score of 1000. They claim that since this mean is higher than the known mean of 896 for all SAT scores, their program must improve SAT scores.
. Question: Is this difference in the mean scores statistically significant? Does SAT Prep truly improve SAT Scores?
.
Investigation 1: What is Normal?
One reason for gathering data is to see which observations are most likely. For instance, when we looked at the raisin data in DoW #3, we were looking to see what the most likely number of raisins was for each brand of raisins. We cannot ever be certain of the exact number of raisins in a box (because it varies) ...
Four square-introduction dewey
Taken from Edmond Public Schools with recommended grade levels added by Dewey Elementary :)
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Populations LabLAB #3, PART I ESTIMATING POPULATION SIZEO.docx
Populations Lab
LAB #3, PART I: ESTIMATING POPULATION SIZE
OBJECTIVE: To estimate population sizes and dynamics, you will be able to:
1. Compare and contrast methods of estimating population size (CLO #1)
2. Explain and use simple mathematical models of population dynamics (CLO #2)
3. Synthesize your research with the primary literature in ecology (CLO #3)
BACKGROUND INFORMATION:
Estimating the size of populations of organisms is a central problem in field ecology. It is one of the most basic pieces of information we can collect and is an important start for other ecological studies and conservation and management efforts. There are several ways to evaluate organism count (pop. size) or density (count/area), which are two means of characterizing populations
Sometimes, it is sufficient to evaluate organism relative abundance (relative representation of a species in a particular location). In that case, an ecologist can use indices. Indices are anything that can be correlated to the number of organisms in a given habitat (e. g., feces pellets, browsed branches, tracks, plant cover, etc.).
When population size is necessary, population estimates can be developed with a number of sampling and mathematical methods. Since it is rarely feasible to count an entire population, ecologists count a portion of the population and then estimate the total population size using mathematical functions. This can be done a number of ways, but in this exercise we will use two of the most common: density methods and mark-recapture methods.
Density method: In this method, ecologists will count the number of individuals in a prescribed area and then scale this measurement up to estimate the whole population size. Transect methods, in which an ecologist traverses a transect and counts individuals at specific locations along the line, are commonly used for plants and occasionally for animals.
Density methods require a few key assumptions:
1. The population is confined to a specific area
2. Individuals are readily detectable
3. Count areas are extensive relative to area occupied by population
Using these assumptions, ecologists use various models to calculate population size. In this lab, you will use a simple Seber (1973) model:
where N = the population estimate, N0 = the average number of organisms found in a plot. And p = the ratio of the individual plot area to total area (e.g. 25 cm2/820 cm2). Once you have calculated No, use the equation above to calculate N.
Confidence intervals provide a measure of the precision of our estimate (population size, N, in this case). A 95% confidence interval is a range of values that is thought to contain the true population size 95% of the time…that is, if you repeat your sampling and confidence interval calculation 100 times, the confidence intervals will capture the true value 95 of those times. To calculate the 95% confidence interval we can simply calculate the upper and lower confidence limits for N0 and then .
4 Solutions To Exercises 4.1 About These Solutions 4.2 Using The Table Of Ran...
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250 words, no more than 500· Focus on what you learned that made.docx
250 words, no more than 500
· Focus on what you learned that made an impression, what may have surprised you, and what you found particularly beneficial and why. Specifically:
· What did you find that was really useful, or that challenged your thinking?
· What are you still mulling over?
· Was there anything that you may take back to your classroom?
· Is there anything you would like to have clarified?
Your Weekly Reflection will be graded on the following criteria for a total of 5 points:
· Reflection is written in a clear and concise manner, making meaningful connections to the investigations & objectives of the week.
· Reflection demonstrates the ability to push beyond the scope of the course, connecting to prior learning or experiences, questioning personal preconceptions or assumptions, and/or defining new modes of thinking.
BELOW ARE LESSON COVERED
· This week's investigations introduce and explore one of the most common distributions (one you may be familiar with): the Normal Distribution. In our explorations of the distribution and its associated curve, we will revisit the question of "What is typical?" and look at the likelihood (probability) that certain observations would occur in a given population with a variable that is normally distributed. We will apply our work with Normal Distributions to briefly explore some big concepts of inferential statistics, including the Central Limit Theorem and Hypothesis Testing. There are a lot of new ideas in this week’s work. This week is more exploratory in nature.
Goals:
· Explore the Empirical Rule
· Become familiar with the normal curve as a mathematical model, its applications and limitations
· Calculate z-scores & explain what they mean
· Use technology to calculate normal probabilities
· Determine the statistical significance of an observed difference in two means
· Use technology to perform a hypothesis test comparing means (z-test) and interpret its meaning
· Use technology to perform a hypothesis test comparing means (t-test) (optional)
· Gather data for Comparative Study Final Project.
·
DoW #5: The SAT & The ACT
Two Common Tests for college admission are the SAT (Scholastic Aptitude Test) and the ACT (American College Test). The scores for these tests are scaled so that they follow a normal distribution.
· The SAT reported that its scores were normally distributed with a mean μ=896 and a standard deviation σ=174
· The ACT reported that its scores were normally distributed with a mean μ=20.6 and a standard deviation σ=5.2.
We have two questions to consider for this week’s DoW:
2. A high school student Bobby takes both of these tests. On the SAT, he achieves a score of 1080. On the ACT, he achieves a score of 30. He cannot decide which score is the better one to send with his college applications.
. Question: Which test score is the stronger score to send to his colleges?
· A hypothetical group called SAT Prep claims that students who take their SAT Preparatory course score higher o.
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Module Five Normal Distributions & Hypothesis TestingTop of F.docx
Module Five: Normal Distributions & Hypothesis Testing
Top of Form
Bottom of Form
·
Introduction & Goals
This week's investigations introduce and explore one of the most common distributions (one you may be familiar with): the Normal Distribution. In our explorations of the distribution and its associated curve, we will revisit the question of "What is typical?" and look at the likelihood (probability) that certain observations would occur in a given population with a variable that is normally distributed. We will apply our work with Normal Distributions to briefly explore some big concepts of inferential statistics, including the Central Limit Theorem and Hypothesis Testing. There are a lot of new ideas in this week’s work. This week is more exploratory in nature.
Goals:
· Explore the Empirical Rule
· Become familiar with the normal curve as a mathematical model, its applications and limitations
· Calculate z-scores & explain what they mean
· Use technology to calculate normal probabilities
· Determine the statistical significance of an observed difference in two means
· Use technology to perform a hypothesis test comparing means (z-test) and interpret its meaning
· Use technology to perform a hypothesis test comparing means (t-test) (optional)
· Gather data for Comparative Study Final Project.
·
DoW #5: The SAT & The ACT
Two Common Tests for college admission are the SAT (Scholastic Aptitude Test) and the ACT (American College Test). The scores for these tests are scaled so that they follow a normal distribution.
· The SAT reported that its scores were normally distributed with a mean μ=896 and a standard deviation σ=174
· The ACT reported that its scores were normally distributed with a mean μ=20.6 and a standard deviation σ=5.2.
We have two questions to consider for this week’s DoW:
2. A high school student Bobby takes both of these tests. On the SAT, he achieves a score of 1080. On the ACT, he achieves a score of 30. He cannot decide which score is the better one to send with his college applications.
. Question: Which test score is the stronger score to send to his colleges?
· A hypothetical group called SAT Prep claims that students who take their SAT Preparatory course score higher on the SAT than the general population. To support their claim, they site a study in which a random sample of 50 SAT Prep students had a mean SAT score of 1000. They claim that since this mean is higher than the known mean of 896 for all SAT scores, their program must improve SAT scores.
. Question: Is this difference in the mean scores statistically significant? Does SAT Prep truly improve SAT Scores?
.
Investigation 1: What is Normal?
One reason for gathering data is to see which observations are most likely. For instance, when we looked at the raisin data in DoW #3, we were looking to see what the most likely number of raisins was for each brand of raisins. We cannot ever be certain of the exact number of raisins in a box (because it varies) ...
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