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Sholpan [36]
3 years ago
12

Find the next two terms in the sequence.

Mathematics
2 answers:
castortr0y [4]3 years ago
7 0
The first one subtracts 9.1 --> -26.6, -35.7
The second one subtracts 35 --> -105, -140
The third one subtracts 9.1 --> -44.8 , -53.9
The fourth one adds 9.1 --> 44.8 , 53.9
The fifth one adds 9.1 --> 37.1 , 46.2

I am sorry I do not have time to do the rest, but just find a pattern between the given terms and apply that to the next terms
Margaret [11]3 years ago
5 0
The first one is arithmetic with CD = -9.1  so the answer is B

Third  one is D

Second question:

a1 = 648 and r = 1/3  so 8th term  = 648 * (1/3)^7  =  8/27
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G(b) = 5b- 9 h(b) = (b - 1)^2 Evaluate. (hog)(-6) =
laiz [17]

Given:

The two functions are:

g(b)=5b-9

h(b)=(b-1)^2

To find:

The value of (h\circ g)(-6).

Solution:

We have,

g(b)=5b-9

h(b)=(b-1)^2

We know that,

(h\circ g)(b)=h(g(b))

(h\circ g)(b)=h(5b-9)

(h\circ g)(b)=[(5b-9)-1]^2

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Putting b=-6, we get

(h\circ g)(-6)=[5(-6)-10]^2

(h\circ g)(-6)=[-39-10]^2

(h\circ g)(-6)=[-49]^2

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3 years ago
A study of the number of business lunches that executives in the insurance and banking industries claim as deductible expenses p
gizmo_the_mogwai [7]

Answer:

t=\frac{9.1-8}{\sqrt{\frac{(1.9)^2}{40}+\frac{(2.1)^2}{50}}}}=2.604  

p_v =2*P(t_{(88)}>2.604)=0.0108

So the p value is a very low value and using any significance level for given \alpha=0.05 always p_v so we can conclude that we have enough evidence to reject the null hypothesis, and there is enough evidence to conclude that the two means are significantly different at 5%

Step-by-step explanation:

Data given and notation

\bar X_{1}=9.1 represent the mean for the sample 1

\bar X_{2}=8 represent the mean for the sample 2

s_{1}=1.9 represent the sample standard deviation for the sample 1

s_{2}=2.1 represent the sample standard deviation for the sample 2

n_{1}=40 sample size for the group 1

n_{2}=50 sample size for the group 2

t would represent the statistic (variable of interest)

Concepts and formulas to use

We need to conduct a hypothesis in order to check if the mean are different , the system of hypothesis would be:

Null hypothesis:\mu_{1} = \mu_{2}

Alternative hypothesis:\mu_{1} \neq \mu_{2}

If we analyze the size for the samples both are higher than 30 and the population deviations are not given, so for this case is better apply a t test to compare means, and the statistic is given by:

t=\frac{\bar X_{1}-\bar X_{2}}{\sqrt{\frac{s^2_{1}}{n_{1}}+\frac{s^2_{2}}{n_{2}}}} (1)

t-test: Is used to compare group means. Is one of the most common tests and is used to determine whether the means of two groups are equal to each other.

Calculate the statistic

We can replace in formula (1) the results obtained like this:

t=\frac{9.1-8}{\sqrt{\frac{(1.9)^2}{40}+\frac{(2.1)^2}{50}}}}=2.604  

Statistical decision

The first step is calculate the degrees of freedom, on this case:

df=n_{1}+n_{2}-2=40+50-2=88

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p_v =2*P(t_{(88)}>2.604)=0.0108

So the p value is a very low value and using any significance level for given \alpha=0.05 always p_v so we can conclude that we have enough evidence to reject the null hypothesis, and there is enough evidence to conclude that the two means are significantly different at 5%

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