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emmasim [6.3K]
3 years ago
14

Find the value of below algebriac expression for x=2,y=-1 and z=2 i. 4x2−3y2+5z24x2−3y2+5z2 ii. 3x3−2x(4yz+5x2)3x3−2x(4yz+5x2) i

ii. 1−4x(yz+3xy)1−4x(yz+3xy)
Mathematics
1 answer:
Advocard [28]3 years ago
8 0

Answer:

i. 33

ii. 1488

iii. 65

Step-by-step explanation:

i. 4x² − 3y² + 5z²

Putting the values x=2, y=-1 and z=2

4(2)² − 3(-1)² + 5(2)²

4×4 − 3×(1)² + 5×(4)

(16) -  (3×1) + (20)

16 -  3+ 20

36 - 3

33

ii. 3x³ − 2x(4yz+5x²)

Putting the values x=2, y=-1 and z=2

[3(2)³ − 2×2(4×(-1)×2 + 5×(2)²)]

[3(8)³ − 2×2(-8 + 5×4)]

[3 ×512 -  2×2(-8 +20)]

[1536 - 4(12)]

[1536 - 48]

1488

iii. 1−4x(yz+3xy)

Putting the values x=2, y=-1 and z=2

[1 - 4 × 2((-1)×2 + 3×2×(-1))]

[1- 8(-2 + (-6))]

[1- 8 (-2 -6)]

[1 - 8(-8)]

[1 +64]

65

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Some scientists believe alcoholism is linked to social isolation. One measure of social isolation is marital status. A study of
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Answer:

1) H0: There is independence between the marital status and the diagnostic of alcoholic

H1: There is association between the marital status and the diagnostic of alcoholic

2) The statistic to check the hypothesis is given by:

\sum_{i=1}^n \frac{(O_i -E_i)^2}{E_i}

3) \chi^2 = \frac{(21-33.143)^2}{33.143}+\frac{(37-41.429)^2}{41.429}+\frac{(58-41.429)^2}{41.429}+\frac{(59-46.857)^2}{46.857}+\frac{(63-58.571)^2}{58.571}+\frac{(42-58.571)^2}{58.571} =19.72

4) df=(rows-1)(cols-1)=(3-1)(2-1)=2

And we can calculate the p value given by:

p_v = P(\chi^2_{2} >19.72)=5.22x10^{-5}

And we can find the p value using the following excel code:

"=1-CHISQ.DIST(19.72,2,TRUE)"

Since the p value is lower than the significance level so then we can reject the null hypothesis at 5% of significance, and we can conclude that we have association between the two variables analyzed.

Step-by-step explanation:

A chi-square goodness of fit test "determines if a sample data matches a population".

A chi-square test for independence "compares two variables in a contingency table to see if they are related. In a more general sense, it tests to see whether distributions of categorical variables differ from each another".

Assume the following dataset:

                    Diag. Alcoholic   Undiagnosed Alcoholic    Not alcoholic    Total

Married                     21                              37                            58                116

Not Married              59                             63                            42                164

Total                          80                             100                          100              280

Part 1

We need to conduct a chi square test in order to check the following hypothesis:

H0: There is independence between the marital status and the diagnostic of alcoholic

H1: There is association between the marital status and the diagnostic of alcoholic

The level os significance assumed for this case is \alpha=0.05

Part 2

The statistic to check the hypothesis is given by:

\sum_{i=1}^n \frac{(O_i -E_i)^2}{E_i}

Part 3

The table given represent the observed values, we just need to calculate the expected values with the following formula E_i = \frac{total col * total row}{grand total}

And the calculations are given by:

E_{1} =\frac{80*116}{280}=33.143

E_{2} =\frac{100*116}{280}=41.429

E_{3} =\frac{100*116}{280}=41.429

E_{4} =\frac{80*164}{280}=46.857

E_{5} =\frac{100*164}{280}=58.571

E_{6} =\frac{100*164}{280}=58.571

And the expected values are given by:

                    Diag. Alcoholic   Undiagnosed Alcoholic    Not alcoholic    Total

Married             33.143                       41.429                        41.429                116

Not Married     46.857                      58.571                        58.571                164

Total                   80                              100                             100                 280

And now we can calculate the statistic:

\chi^2 = \frac{(21-33.143)^2}{33.143}+\frac{(37-41.429)^2}{41.429}+\frac{(58-41.429)^2}{41.429}+\frac{(59-46.857)^2}{46.857}+\frac{(63-58.571)^2}{58.571}+\frac{(42-58.571)^2}{58.571} =19.72

Part 4

Now we can calculate the degrees of freedom for the statistic given by:

df=(rows-1)(cols-1)=(3-1)(2-1)=2

And we can calculate the p value given by:

p_v = P(\chi^2_{2} >19.72)=5.22x10^{-5}

And we can find the p value using the following excel code:

"=1-CHISQ.DIST(19.72,2,TRUE)"

Since the p value is lower than the significance level so then we can reject the null hypothesis at 5% of significance, and we can conclude that we have association between the two variables analyzed.

7 0
4 years ago
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