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3 years ago

X + 3= 8x -11

Mathematics

1 answer:

lapo4ka [179]3 years ago

6 0

The answer is x=2

explanation:

2+3=5

8 times 2 is 16, minus 11=5

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An Ontario lottery has the following structure, the first person drawn from the names wins $15 000. Each subsequent person drawn

elixir [45]

The first four terms are : 15000, 14850, 14700, 14550
a = 15000 ; d = -150
The explicit formula is : $a_{n} = - 150n \: + 15150$

The first term of the sequence, a = 15,000

Each subsequent winner gets $150 less

Hence, the common difference, d = - $150

The first four terms :

First term, a1 = $15000

Second term, a2 = a - d = $15000 - $150 = $14850

Third term, a3 = a2 - d = $14850 - $150 = $14700

Fourth term, a4 = a3 - d = $14700 - $150 = $14550

a, for the sequence is the first term = $15000

d, for the sequence is the common $150 (difference between successive wins).

Explicit formula for the general term :

$a_{n} \: = nd \: + c$

For n = 1

$15000 = 1( - 150) + c$

$15000 = - 150 + c$

$c = 15150$

Hence, the explicit formula for the nth term is :

$a_{n} \: = - 150n \: + 15150$

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3 years ago

What can I add to get -6?

krok68 [10]

So what you would need to add to get -6 is -5-1 then your answer would be -6 hope this helps!

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a. esteban-perez and j. m. morales ´ , distributionally robust stochastic programs with side information based on trimmings, mat

sleet_krkn [62]

Distributionally robust stochastic programs with side information based on trimmings

This is a research paper whose authors are Adrián Esteban-Pérez and Juan M. Morales.

Abstract:

We look at stochastic programmes that are conditional on some covariate information, where the only knowledge of the possible relationship between the unknown parameters and the covariates is a limited data sample of their joint distribution. We build a data-driven Distributionally Robust Optimization (DRO) framework to hedge the decision against the inherent error in the process of inferring conditional information from limited joint data by leveraging the close relationship between the notion of trimmings of a probability measure and the partial mass transportation problem.
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Conclusions:

We used the relationship between probability reductions and partial mass transit in this study to give a straightforward, yet powerful and creative technique to expand the usual Wasserstein-metric-based DRO to the situation of conditional stochastic programming. In the process of inferring the conditional probability measure of the random parameters from a limited sample drawn from the genuine joint data-generating distribution, our technique generates judgments that are distributionally resilient to uncertainty. In a series of numerical tests based on the single-item newsvendor issue and a portfolio allocation problem, we proved that our strategy achieves much higher out-of-sample performance than several current options. We backed up these actual findings with theoretical analysis, demonstrating that our strategy had appealing performance guarantees.

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Write an inequality to represent each sentence. Use n for the variable.

Zepler [3.9K]

Answer:

17>n is the correct answer

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