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trasher [3.6K]
3 years ago
15

Which of the statements below are true? Select all that apply. A correlation of r = .92 indicates a strong, positive correlation

. Correlation must be between 0 and 1. A correlation of r = -.17 indicates a strong, negative correlation. A correlation of r = .01 means there is no significant correlation. Correlation must be between -1 and 1. Correlation is a numeric measure of the strength and the direction between two categorical variables.
Mathematics
2 answers:
castortr0y [4]3 years ago
6 0
The correct answer for the question that is being presented above is this one: "Correlation must be between 0 and 1; A correlation of r = .01 means there is no significant correlation; Correlation must be between -1 and 1; <span>Correlation is a numeric measure of the strength and the direction between two categorical variables."</span>
daser333 [38]3 years ago
6 0

Answer with explanation:

Correlation Coefficient (r) ,measures the relation between two variables written in the form of ordered pair.

→If ordered pair (x,y) represents two variables , correlated with each other

that is with increase in x, y also increases, or vice versa ,then r would be positive.

And if , with increase in x, y decreases or vice versa, then r will be negative.

→ -1 ≤ r ≤1.

The Correct statements are

1. →A correlation of r = .92 indicates a strong, positive correlation.

4.→A correlation of r = .01 means there is no significant correlation.

5.→ Correlation must be between -1 and 1.

6.→Correlation is a numeric measure of the strength and the direction between two categorical variables.

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The College Board SAT college entrance exam consists of three parts: math, writing and critical reading (The World Almanac 2012)
Wittaler [7]

Answer:

Yes, there is a difference between the population mean for the math scores and the population mean for the writing scores.

Test Statistics =   \frac{Dbar - \mu_D}{\frac{s_D}{\sqrt{n} } } follows t_n_-  _1 .

Step-by-step explanation:

We are provided with the sample data showing the math and writing scores for a sample of twelve students who took the SAT ;

Let A = Math Scores ,B = Writing Scores  and D = difference between both

So, \mu_A = Population mean for the math scores

       \mu_B = Population mean for the writing scores

 Let \mu_D = Difference between the population mean for the math scores and the population mean for the writing scores.

            <em>  Null Hypothesis, </em>H_0<em> : </em>\mu_A = \mu_B<em>     or   </em>\mu_D<em> = 0 </em>

<em>      Alternate Hypothesis, </em>H_1<em> : </em>\mu_A \neq  \mu_B<em>      or   </em>\mu_D \neq<em> 0</em>

Hence, Test Statistics used here will be;

            \frac{Dbar - \mu_D}{\frac{s_D}{\sqrt{n} } } follows t_n_-  _1    where, Dbar = Bbar - Abar

                                                               s_D = \sqrt{\frac{\sum D_i^{2}-n*(Dbar)^{2}}{n-1}}

                                                               n = 12

Student        Math scores (A)          Writing scores (B)         D = B - A

     1                      540                            474                                   -66

     2                      432                           380                                    -52  

     3                      528                           463                                    -65

     4                       574                          612                                      38

     5                       448                          420                                    -28

     6                       502                          526                                    24

     7                       480                           430                                     -50

     8                       499                           459                                   -40

     9                       610                            615                                       5

     10                      572                           541                                      -31

     11                       390                           335                                     -55

     12                      593                           613                                       20  

Now Dbar = Bbar - Abar = 489 - 514 = -25

 Bbar = \frac{\sum B_i}{n} = \frac{474+380+463+612+420+526+430+459+615+541+335+613}{12}  = 489

 Abar =  \frac{\sum A_i}{n} = \frac{540+432+528+574+448+502+480+499+610+572+390+593}{12} = 514

 ∑D_i^{2} = 22600     and  s_D = \sqrt{\frac{\sum D_i^{2}-n*(Dbar)^{2}}{n-1}} = \sqrt{\frac{22600 - 12*(-25)^{2} }{12-1} } = 37.05

So, Test statistics =   \frac{Dbar - \mu_D}{\frac{s_D}{\sqrt{n} } } follows t_n_-  _1

                            = \frac{-25 - 0}{\frac{37.05}{\sqrt{12} } } follows t_1_1   = -2.34

<em>Now at 5% level of significance our t table is giving critical values of -2.201 and 2.201 for two tail test. Since our test statistics doesn't fall between these two values as it is less than -2.201 so we have sufficient evidence to reject null hypothesis as our test statistics fall in the rejection region .</em>

Therefore, we conclude that there is a difference between the population mean for the math scores and the population mean for the writing scores.

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Lisa made a shirt using 1/3 m of blue fabric and 3/5 m of red fabric how many meters of fabric did she use in all
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Answer: 14/15 of a meter

Step-by-step explanation:

5 and 3 LCM is 15.

3/5 x 3 + 1/3 x 5= 9/15 + 5/ 15 = 14/15

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Answer:

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Hence,

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Answer:

m = rise/run = 4/5.

Step-by-step explanation:

This line goes throught the "exact" grid intersections (-2, 0) and (3, 4).  As we move from the first point to the second, we see that x increases by 5 (this is the 'run') and y increases by 4 (this is the 'rise').  Thus, the slope of this line is m = rise/run = 4/5.

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