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Oksanka [162]
3 years ago
7

What's the explicit formula for the sequence :")

Mathematics
1 answer:
zzz [600]3 years ago
7 0

Hello from MrBillDoesMath!

Answer:

a(n) = 12 - 3(n-1)          , n = 1,2,3.,,



Discussion:

The terms are 12, 9, 6, 3  so we are apparently subtracting 3 from each succeeding term. . Hence

a(n) = 12 - 3(n-1)          , n = 1,2,3.,,


Thank you,

MrB

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Which of the following is not a postulate of Euclidean geometry?
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It’s C, All equilateral triangles have interior angles equal to 60 degrees

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3 years ago
Suppose Carla has $7000 to invest. Which investment yields the greater return over 4 years: 7% compounded quarterly or 6.85% com
tatiyna

Answer:

The correct answer is B. The rate of 7% compounded quarterly is better.

Step-by-step explanation:

In the case of investment at 7% compounded quarterly, the final result after 4 years of investment arises from the following calculation:

X = 7000 x (1 + 0.7 / 3) 4x3

X = 9,232.16

Therefore, after 4 years of investment, the amount in the account would be $ 9,232.16.

In turn, in the case of the investment at 6.85% compounded monthly, the final result after the same investment period arises from the following calculation:

X = 7000 x (1 + 0.685 / 12) 4x12

X = 9,199.33

Thus, in this case, the amount in the account after 4 years of investment would be $ 9,199.33.

8 0
3 years ago
What fractions are equivalent to 2/3
just olya [345]
4/6
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4 0
3 years ago
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Consider the following data on x = rainfall volume (m^3) and y = runoff volume (m^3) for a particular location.
nydimaria [60]

Answer:

Step-by-step explanation:

From the given information:

x                     y                     xy                   x²                        y²

4                     4                     16                  16                        16

12                   10                   120                 144                     100

14                   13                   182                  196                     169

20                 15                   300                 400                    225

23                 15                   345                  529                    225

30                 25                 750                   900                    625

40                 27                 1080                 1600                    729

48                 44                 2112                  2304                  1936

55                 38                 2090               3025                   1444

67                 46                 3082               4489                    2116

72                 53                 3816                 5184                  2809

85                 71                 6035                 7225                  5041

96                 82               7872                 9216                   6724

112                 99               11088                12544                 9801

127                 101              12827                16129                10201

\sum _{xi} = 805      \sum_{yi} = 643    \sum_{x_iy_I}= 51715   \sum_{x_i^2}= 63901    \sum_{y_i^2} = 42161

The least-square regression equation is: \hat y = b_o+b_1 x

b_1 = \dfrac{n \sum xy - ( \sum _x) ( \sum_y)}{n \sum x^2 - ( \sum x)^2}

b_1 = \dfrac{15(51715) - (803) (643)}{15(63901)-(805)^2}

b_1 = \dfrac{775725-516329}{958515-648025}

b_1 = \dfrac{259396}{310490}

b₁ = 0.835440

∴ Slope term, b₁ = 0.835

SS_{XX} = \sum x^2 - \dfrac{(\sum x)^2}{n}= 63901 - \dfrac{(805)^2}{15}=20699.33

SS_{yy} = \sum y^2 - \dfrac{(\sum y)^2}{n }= 42161 - \dfrac{(643)^2}{15}= 14597.73

SS_{xy} = \sum xy - \dfrac{(\sum x) (\sum y)}{n}= 51715 - \dfrac{(803)(643)}{15}= 17293.067

SST = SS_{yy}= 14597.73

SSR = \dfrac{SS_{xy}^2}{SS_{xx}}= \dfrac{17293.067^2}{20699.33}=14447.34

SSE = SST - SSR = 14597.73 - 14447.34 = 150.39

The hypothesis test for the significance of \beta_1 is:

H_o: \beta_1 = 0 \\ \\ H_1: \beta_1 \ne 0

Significance level ∝ = 1 - 0.95 = 0.05

The sample slope b_1 = 0.835440

Test \ statistic = t_{observed} = \dfrac{b_1-0}{\sqrt{\dfrac{SSE}{(n-2)SS_{xx}}}}

t_{o} = \dfrac{0.835440-0}{\sqrt{\dfrac{150.39}{(15-2)20699.33}}}

t_{o} = \dfrac{0.835440}{\sqrt{\dfrac{150.39}{269091.29}}}

t_o = 35.339

Degree of freedom df = n - 2

df = 15 -2

df = 13

Using the Excel formula to determine the P_value.

P-value = P(t, \Big|35.339 \Big|)

P-value = 2 × t.dist(35.339,13,1)

P-value = 0.0000

P-value = 0

Critical value: t_{critical} = t_{\alpha/2,df} = t_{0.05/2,13}= 2.160

Rejection region: To reject H_o; if \Big | t_o \Big | > t_c

Decision: Since \Big | t_o \Big | > t_c; we reject  H_o

Conclusion: There is enough evidence to conclude that the linear relationship between x & y

Thus; we reject H_o & there is a useful linear relationship between x & y.

The 95% C.I for slope is given by the equation:

=b_1 \pm t_{(\alpha/2,n-2)} \sqrt{\dfrac{SSE}{n-2}}\sqrt{\dfrac{1}{SS_{xx}} }

=0.835440 \pm 2.160 \sqrt{\dfrac{150.39}{15-2}}\sqrt{\dfrac{1}{20699.33} }

= 0.835440 ± 2.160 (3.40124)(0.006951)

= 0.835440 ± 0.0511

= (0.835440 - 0.0511, 0.835440 + 0.0511)

= (0.78434, 0.88654)

= (0.784, 0.887)   to three decimal places.

∴ 95% C.I of slope = \mathbf{( 0.784 < \beta_1 < 0.887) \ to \ 3 \ d.p}

6 0
3 years ago
Jimmy is a carpenter. The graph shows the number of chairs that he assembles and the amount of time it takes him.
alexdok [17]

Answer:

36 chairs assembled

Step-by-step explanation:

I don't think that the equation you gave, c = h, is accurate based on the graph.  Based off the graph, I will make a different equation.  

c = 8h

c = (8)(4.5)

c = 36

5 0
3 years ago
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