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Oksana_A [137]
3 years ago
5

Find the least number by which 243 must be divided to make it a perfect square.

Mathematics
1 answer:
Anarel [89]3 years ago
3 0

Is 243 a perfect square number? A number is a perfect square (or a square number) if its square root is an integer; that is to say, it is the product of an integer with itself. Here, the square root of 243 is about 15.588. Thus, the square root of 243 is not an integer, and therefore 243 is not a square number.

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Martin’s neighbors pat him $8 per week to walk their dog. He saves his money for 5 weeks. Martin buys a new bike helmet for $37.
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7 0
3 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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