Answer:
The 4 t h term is f(4) = 143
Step-by-step explanation:
<em>Explanation</em>:-
Given function f(1) = -4
Given 'nth' term is f(n) = -3f(n-1) +5
Put n =2 <em> f(2) = -3 f(2-1) +5</em>
= -3 f(1) +5
= -3 (-4) +5
= 12 +5
f(2) = 17
put n= 3
f(n) = -3f(n-1) +5
<em> f(3) = -3 f(3-1) +5</em>
= -3f(2) +5
= -3(17) +5
= -51+5
f(3) = -46
Put n=4
f(n) = -3f(n-1) +5
<em> f(4) = -3f(4-1) +5</em>
<em> f(4) = -3f(3)+5</em>
f(4) = -3(-46)+5
f(4) = 138 +5
f(4) = 143
<u><em>Final answer</em></u>:-
<em>The 4 t h term is f(4) = 143</em>
We have
To simplify it we can divide numerator and denumerator by the same number (the greatest possible is the best)
- its the simples form..
Answer:
Jermey is not correct because abouslte value is always postive
Step-by-step explanation:
The possible outcomes of a random experiment and the probability of each outcome is called "a Probability Distribution."
<h3>What is a Probability Distribution?</h3>
A probability is a statistical formula that indicates all of the potential values and probability distributions for a random variable within a specified range.
Some characteristics regarding the Probability Distribution are-
- The range will be bounded by the minimum and greatest possible values, but the precise location of the possible value just on probability distribution relies on a number of factors.
- These variables include the mean (average), standard deviation, skewness, & kurtosis of the distribution.
- Although other regularly used probability distributions exist, the normal distribution, called "bell curve," is perhaps the most common.
- Typically, the technique of generating data for a phenomenon will influence its probability distribution. This is known as the probability density function.
- Likelihood distributions can also be used to generate cumulative distribution functions (CDFs), that cumulatively build up the probability of occurrences and always begin at zero and end at 100%.
To know more about Probability Distribution, here
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