бизнесийн статистик хичээлийн нэмэлт даалгавар
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The document contains 10 questions about calculating Pearson correlation coefficients from data sets involving various attributes of groups of 10 friends such as their heights, weights, math scores, times to run 100m, and waist sizes. Questions 1-2 ask about describing correlations from scatter plots while questions 3-10 involve calculating the actual Pearson correlation coefficient values from provided data tables relating two attributes at a time.
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Ppt 1
1) A median of a triangle is a line drawn from a vertex to the midpoint of the side opposite that vertex.
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Part A
Some questions in Part A require that you access data from
Statistics for People Who (Think
T
hey) Hate Statistics
.
This data is available on the student website under the Student Text Resources link.
1.
Use the following data to answer Questions 1a and 1b.
Total no. of problems correct (out of a possible 20)
Attitude toward test taking (out of a possible 100)
17
94
13
73
12
59
15
80
16
93
14
85
16
66
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19
91
a.
Compute the Pearson product-moment correlation coefficient by hand and show all your work.
b.
Construct a scatterplot for these 10 values by hand. Based on the scatterplot, would you predict the correlation to be direct or indirect? Why?
2.
Rank the following correlation coefficients on strength of their relationship (list the weakest first):
+.71
+.36
–.45
.47
–.62
3.
Use IBM
®
SPSS
®
software to determine the correlation between hours of studying and grade point average for these honor students. Why is the correlation so low?
Hours of studying
GPA
23
3.95
12
3.90
15
4.00
14
3.76
16
3.97
21
3.89
14
3.66
11
3.91
18
3.80
9
3.89
4.
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Variable
X
Variable
Y
Type of correlation
Correlation being computed
Nominal (voting preference, such as Republican or Democrat)
Nominal (gender, such as male or female)
Phi coefficient
The correlation between voting preference and gender
Nominal (social class, such as high, medium, or low)
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Rank biserial coefficient
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Interval (grade point average)
Point biserial
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Ordinal (height converted to rank)
Ordinal (weight converted to rank)
Spearman rank correlation coefficient
The correlation between height and weight
Interval (number of problems solved)
Interval (age in years)
Pearson product-moment correlation coefficient
The correlation between number of problems solved and the age in years
5.
When two variables are correlated (such as strength and running speed), it also means that they are associated with one another. But if they are associated with one another, then why does one not cause the other?
6.
Given the following information, use Table B.4 in Appendix B of
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a.
The correlation between speed and strength for 20 women is .567. Test these results at the .01 level using a one-tailed test.
b.
The correlation between the number co.
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Question 1
The time required for a citizen to complete the 2000 U.S. Census "long" form is normally distributed with a mean of 40 minutes and a standard deviation of 10 minutes. What proportion of the citizens will require less than one hour?
Question 2
If the random variable Z has a standard normal distribution, then P(Z ≤ -1.37) is
Question 3
Bob's z-score for the last exam was 1.52 in Prof. Axolotl's class BIO 417 "Life Cycle of the Ornithorhynchus". Bob said, "Oh, good, I'm in the top 10%." Is he right?
Question 4
If arrivals occur at a mean rate of 1.6 events per minute, the exponential probability of waiting less than 1 minute for the next arrival is
Question 5
The lengths of brook trout caught in a certain Colorado stream have a mean of 14 inches and a standard deviation of 3 inches. The first quartile for the lengths of brook trout would be
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Assume that X is normally distributed with a mean μ= $64. Given that P(X ≥$75) = 0.2981, we can calculate that the standard deviation of X is approximately
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If arrivals follow a Poisson distribution with mean 1.2 arrivals per minute, find the 75th percentile of waiting times (i.e., 75 percent below).
Question 8
The MPG (miles per gallon) for a certain compact car is normally distributed with a mean of 31 and a standard deviation of 0.8. What is the probability that the MPG for a randomly selected compact car would be less than 32?
Question 9
A letter is mailed to a sample of 500 homeowners. Based on past experience, the probability of an undeliverable letter is 0.06. The normal approximation to the probability of 40 or more undeliverable letters is
Question 10
Which model best describes your waiting time until you get the next non-working web URL ("This page cannot be displayed") as you click on web sites for Florida condo rentals?
10. The Pearson r and Spearman rho correlation coefficients are related. Is this statement correct? Explain.
15. In a large introductory sociology course, a professor gives two exams. The professor wants to determine whether the scores students receive on the second exam are correlated with their scores on the first exam. To make the calculations easier, a sample of eight students is selected. Their scores are shown in the accompanying table.
Student Exam 1 Exam 2
1 60 60
2 75 100
3 70 80
4 72 68
5 54 73
6 83 97
7 80 85
8 65 90
a. Construct a scatter plot of the data, using exam 1 score as the X variable. Does the relationship look linear?
b. Assuming a linear relationship exists between scores on the two exams, compute the value for Pearson r.
c. How well does the relationship account for the scores on exam 2?
...
Day 3 descriptive statistics
This slides introduce the descriptive statistics and its differences with inferential statistics. It also discusses about organizing data and graphing data.
Scatter diagrams and correlation
Scatter diagrams, strong and weak correlation, positive and negative correlation, lines of best fit, extrapolation and interpolation. Aimed at UK level 2 students on Access and GCSE Maths courses.
4 CREATING GRAPHS A PICTURE REALLY IS WORTH A THOUSAND WORDS4 M.docx
4 CREATING GRAPHS A PICTURE REALLY IS WORTH A THOUSAND WORDS
4: MEDIA LIBRARY
Premium Videos
Core Concepts in Stats Video
· Examining Data: Tables and Figures
Lightboard Lecture Video
· Creating a Simple Chart
Time to Practice Video
· Chapter 4: Problem 3
Difficulty Scale
(moderately easy but not a cinch)
WHAT YOU WILL LEARN IN THIS CHAPTER
· Understanding why a picture is really worth a thousand words
· Creating a histogram and a polygon
· Understanding the different shapes of different distributions
· Using SPSS to create incredibly cool charts
· Creating different types of charts and understanding their application and uses
WHY ILLUSTRATE DATA?
In the previous two chapters, you learned about the two most important types of descriptive statistics—measures of central tendency and measures of variability. Both of these provide you with the one best number for describing a group of data (central tendency) and a number reflecting how diverse, or different, scores are from one another (variability).
What we did not do, and what we will do here, is examine how differences in these two measures result in different-looking distributions. Numbers alone (such as M = 3 and s = 3) may be important, but a visual representation is a much more effective way of examining the characteristics of a distribution as well as the characteristics of any set of data.
So, in this chapter, we’ll learn how to visually represent a distribution of scores as well as how to use different types of graphs to represent different types of data.
CORE CONCEPTS IN STATS VIDEO
Examining Data: Tables and Figures
X-TIMESTAMP-MAP=LOCAL: Examining data helps find data entry errors, evaluate research methodology, identify outliers, and determine the shape of a distribution in a data set. Researchers typically examine collected data in two ways, by creating tables and figures. Imagine you asked a group of friends to rate a movie they've seen on a one to five scale. A table helps identify the variable and the possible values of the variable. The sample size, often referred to as n, is 14 because there are ratings reported from 14 people. This is how large the total sample is. From this, we can determine how many in the sample have each value of the variable. We can also determine the percentage that the sample has of each possible value. Figures display variables from the table. Nominal and ordinal variables can be depicted with bar charts, while interval and ratio variables can be depicted using histograms and frequency polygons. For this data set, we can use a bar chart. Distributions of data can be characterized along three aspects or dimensions, modality, symmetry, and variability. In a unimodal distribution, a small range of values has the greatest frequency or mode of the set. However, it's possible for a distribution to have more than one mode. For a bimodal distribution, we see two values that seem to occur w.
Practice Test 1
Please Subscribe to this Channel for more solutions and lectures
http://www.youtube.com/onlineteaching
Elementary Statistics Practice Test 1
Module 1: Chapters 1-3
Chapter 1: Introduction to Statistics.
Chapter 2: Exploring Data with Tables and Graphs.
Chapter 3: Describing, Exploring, and Comparing Data.
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