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sladkih [1.3K]
3 years ago
15

Which statements are true about the linear inequality y > Three-fourthsx – 2? Select three options.

Mathematics
2 answers:
bekas [8.4K]3 years ago
6 0

Answer:

Step-by-step explanation:

A,C,E is your answer.

Vilka [71]3 years ago
5 0

Answer:

Step-by-step explanation:

i) the given linear inequality is y > \frac{3}{4} x - 2

ii) the first statement is NOT TRUE. the slope of the is \frac{3}{4}.

iii) the second statement is NOT TRUE. The area above the line is shaded.

iv) the third statement is NOT TRUE. (0,0) is not a solution to the inequality.

v) the fourth statement is TRUE.

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Convert the length as indicated What is 2600 cm= ft
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Help with 35 to 40, don’t know if I am right
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Step-by-step explanation:

35. 1000 m / 1 km = 10³

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4 0
4 years ago
The data below shows the selling price (in hundred thousands) and the list price (in hundred thousands) of homes sold. Construct
fredd [130]

Answer:

Since the calculated t= 7.8120 falls in the critical region ≥ 2.306 we reject H0 and conclude that there is a linear correlation between the two variables.

Step-by-step explanation:

We see that r²= 0.981 and r= 0.995 from the figure .

The P- value is less than 0.05  which indicates that the two variables are linearly correlated.

Set up the hypothesis as

H0: β= 0 i.e the two variables X and Y are not related

Ha: β≠0 i.e the two variables are related

The significance Level is set at ∝=0.05

The test statistic , if H0 is true is

t= b/sb

where sb² = s²yx / ∑( x-x`)² = ∑( y-y`)²/n-2 ∑( x-x`)²

assuming that the distribution of Yi for each Xi is normal with the same mean and the same standard deviation , the statistic t conforms to the Student's t distribution with n-2= 8 degrees of freedom

(X - x`)2                 (X - x`)(Y - y`)                       (Y - y`)2

265.69                   259.17                         15.9²=252.81

7174.09                 6953.87                       -82.1²=6740.41

75.69                       87.87                            -10.1=102.01

2052.09                 1671.57                           36.9²=1361.61

4529.29                 5848.37                        86.9²=7551.61

8335.69                7294.87                          79.9²=6384.01

4998.49                5380.27                        -76.1²=5791.21

1069.29                 1016.97                          -31.1=967.21

1043.29                   1159.57                         35.9²=1288.81

<u>3102.49                    3124.77                        -56.1²=3147.21</u>

<u>SS: 32646.1            SP: 32797.3                        33,586.9</u>

<u />

Sum of X = 3877

Sum of Y = 3991

Mean X = 387.7

Mean Y = 399.1

Sum of squares (SSX) = 32646.1

Sum of products (SP) = 32797.3

b = SP/SSX = 32797.3/32646.1 = 1.00463

a = Y` - bX `= 399.1 - (1*387.7) = 9.60437

Syx= √∑(y-y`)²/n-2= 33,586.9/8= 4198.3625

sb= syx/ √∑(x-x`)²=4198.3625/32646.1 =0.12860

Putting the values in the regression equation

ŷ = bX + a

ŷ = 1.00463X + 9.60437

The critical region is t ≥ t (0.025) (8)= 2.306

t= b/ sb= 1.00463/ 0.12860=7.8120

Since the calculated t= 7.8120 falls in the critical region ≥ 2.306 we reject H0 and conclude that there is a linear correlation between the two variables.

4 0
3 years ago
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