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For the following data the value of SSE = 0.4130.
y. x dependent variable. independent variable 15. 4 17. 6 23. 2 17. 4
The y intercept is
Intro stats question. - Yahoo! Answers. Best Answer: Ho: mew=150 ft Ha: mew< 150 ft z = (138 - 150)/(15/sqrt(100)) = -8 a z score of -8 gives you a p value of basically zero you have strong
Intro to Stats Question 29 - YouTube. For the following data the value of SSE = 0.4130. y. …. x dependent variable..… independent variable 15..… 4 17..… 6 23..… 2
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Intro Stats Technology Update, 3e. Best Answer: yes P (134.0604 < x < 141.9396 ) = P (-2.6264 < z < 2.6264 ) = 99% C.I. d.f. = 99
Practice Questions for Business Statistics - Georgia. Intro Stats Technology Update, 3e [Skip Navigation] Welcome: Data Sets: Student Supplements [Skip Breadcrumb Navigation] Home: Intro Stats Technology Update
Amazon.com: Intro Stats (9780201709100): Richard D.. From any chapter's list of question teasers, Practice Questions for Business Statistics. Return to Introduction page. Chapter: Descriptive Statistics I:
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An introduction to statistics. Includes sampling, data display, measures of central tendency, variability, and position; random variables, probability, probability distributions; sampling distributions, assessing normality, confidence intervals, hypothesis testing, ANOVA, and regression. Use of the statistics software R is taught throughout the course.Announcements
Final grades have been posted. The solutions to the final exam are now on the website. Have a good summer and thanks for all your hard work this semester. –AnthonyCourse Info
All homework is due at the beginning of class on Tuesday. Thus, homework assigned on Tuesday and Thursday is due at the beginning of class on the following Tuesday.
Introductory Material. (Sections 1.1-1.4)
In Class Survey: Sexual Partners Survey (encrypted connection) (Do not submit this until instructed to do so.)
Special Home Work Complete within 24 hours :
Home Work (Due next Tuesday)
Summarizing & graphing data. (Sections 2.1-2.4)
Sec 2.2: 1-17 odds (do 17 by hand)
Additional Problem for 2.3: Use R to make two histograms: one of the male heights and of the female heights in the Appendix B Data Set 1 ( Mhealth and Fhealth tables in R). Include both of the histograms in your HW. Then write a paragraph discussing the differences between the male and female heights that you can see from the histograms (ie. center, variation, shape, outliers, min, max). Do either of the histograms have a distribution that is approximately normal?
HINTS: If you are having trouble getting the book data, see the R intro lecture or look at the back of the quick reference sheet. See the top part of this page to download the data sets.
Sec 2.4: 1-4, 9 (use R), 13 (just sketch by hand), 17 (use R), 19 (use R)
Hint for 19: to make a plot with Both lines and points rather than a scatter plot use the optional argument type="b" for the plot function. ex. plot(t, y, type="b"). The time vector t goes from 1990 to 2000. A quick way to make t is to use this shortcut: t=1990:2000 .
Homework: (If you need more explanation and practice with summation notation: see this page )
Measures of center. (Sections 3.1-3.2)
Sec 3.2: 1-9 odds, 13, 15, 21, 23, 25, 29 (Use R if the problem has TI by it from now on.)
Hint for 21: to get the first set of differences use:
You can find the second set of differences in the same way once you figure out the correct column name. (I admit the author’s column names are not that good).
Hint for 23: to get the pennies for before 1983:
To find the post 1983 pennies use the same method but take a look at the Coins table to see what they are called and then modify the above statement.
Hint on 29 b: mean(x, trim=0.10)
Measures of variation. (Sections 3.3)
Relative standing and exploratory data analysis. (Sections 3.4-3.5)
Sec 3.4: 1, 5, 7, 9, 11, 13-27 odds
Additional problem: Use the following code to make two boxplots for comparing gender against bear weight and length. Then use the boxplots to discuss and compare the distribution of lengths and weights of bears in terms of their gender. (Make sure the book data is loaded into R first)
Descriptive Statistics: Case Study.
Probability I: Addition rule. (Sections 4.1-4.3)
Ever wonder how to finish your statistics homework real fast? Or you just want a quick way to verify your tedious calculations in your statistics class assignment. We provide an answer here by solving statistics exercises with R.
Here, you will find statistics problems similar to those found in popular college textbooks. The R solutions are short, self-contained and requires minimal R skill. Most of them are just a few lines in length. With simple modifications, the code samples can be turned into homework answers. In additional to helping with your homework, the tutorials will give you a taste of working with statistics software in general, and it will prove invaluable in the success of your career.
We have included separate introductory tutorials for basic R concepts. The topics are by no means comprehensive. Nevertheless, even if you are not familiar with R, you can go through just the first R Introduction page. Then go straight to the statistics tutorials, and only come back for reference as needed.
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