MATH 221 DeVry Complete Week Discussions Package

admin   June 30, 2017   Comments Off on MATH 221 DeVry Complete Week Discussions Package

MATH 221 DeVry Complete Week Discussions Package

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MATH 221 DeVry Complete Week Discussions Package

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MATH 221 DeVry Complete Week Discussions Package

MATH 221 DeVry Week 1 Discussion Latest

There are lots of “helps” available in this course. Please find one and tell us why it will be useful for you.

Then give careful directions for how to find that “help.”

Be sure to look in the left hand navigation area and also on the upper toolbar as well as in MSL.

Try to find one which hasn’t already been mentioned.

 

MATH 221 DeVry Week 2 Discussion Latest

A regression equation can be graphed. The graph will go uphill as we look at it going from the left to the right; or it will go downhill as we look at it going from the left to the right; or it will be parallel to the x-axis.

Take a look at several examples in the text or in the Homework and ponder for a while.

Then write a very short idea about what’s going on with correlation (consider the r-value), with slope, and anything else you might notice.

Rather than being redundant, please read the ideas your classmates post and comment or add to what they observed.

 

MATH 221 DeVry Week 3 Discussion Latest

Probability and Odds (graded)

Please watch for a new question each day. Please post 3 times minimum.

And be sure to follow the post on 3 different days requirement as well as the 1st post before midnight Wednesday requirement

 

MATH 221 DeVry Week 4 Discussion Latest

Discrete Probability Variables (graded)

There will be a new question each day. Be sure to post on 3 different days.

If I can count it, then it’s discrete. If I can measure it, then it’s continuous.

Please keep these 2 statements in mind as we study random variables.

For today’s post please give an example of a discrete random variable.

  1. If I have 8 cans of coca cola in my refrigerator, that’s a discrete random variable — I can count them. But, if I say that I have 12 ounces in each can, that’s continuous because that’s a measurement. And I can’t really say that it’s 12 ounces. It might be 12. 1 or 11.9 or it could even be 12.05 or 11.95. Getting more accurate it could be 12.00001 or 11.99999. And that’s why we call it continuous — on the number line I can always get a little closer than I was a moment ago.

 

MATH 221 DeVry Week 5 Discussion Latest

Interpreting Normal Distributions (graded)

Please look for a new question each day. Please post on 3 different days.

A skill which will be tremendously important in the coming weeks is sketching a normal curve. And to sketch it we need to draw the x-axis accurately.

Here’s one for a curve when the mean is 0 and the standard deviation is 1.

_____-3_____-2_____-1_____*0*_____+1_____+2_____+3_____

And here’s one for a curve when the mean is 40 and the standard deviation is 4.

_____28_____32_____36____*40*____44_____48_____52_____

And here’s another for a curve when the mean is 10 and the standard deviation is 6.

_____-8_____-2_____+4_____*10*_____16_____22_____28_____

For today’s post please find a normal distribution in the text or in MSL and sketch the appropriate x-axis.

 

MATH 221 DeVry Week 6 Discussion Latest

Confidence Interval Concepts (graded)

Please watch for a new question each day. Be sure to post on 3 different days.

There are many online calculators for confidence intervals.

Find one. Use it. Compare your answer with an answer from one of the examples in the book (that way you’ll know if it is correct). Then share the URL with us and talk about how easy or hard it is to use.

 

MATH 221 DeVry Week 7 Discussion Latest

Rejection Region (graded)

Please watch for a new question each day. Be sure to post on 3 different days.

How is the rejection region defined, and how is that related to the p value?