Joan will not score more than 6 points in the game
1 answer:
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Answer:
The answer to your question is below
Step-by-step explanation:
Data
function f(x) = x² + 2x - 8
-See the graph below
1) x-intercepts
We observe in the graph that there are no x-intercepts.
2) y-intercepts
We observe in the graph that the y-intercept is (0, 8). Point A
3) axis of symmetry
The axis of symmetry is the line that divides the parabola into two equal parts. This line is x = -1 (blue line)
4) The vertex is the lowest point of the parabola, this point is (-1, 7)
Point B in the graph.
Answer:
The x-intercept of this equation is at the point (0,0).
Step-by-step explanation:
The graph starts at the origin because the log of 4^0 = 0.
I graphed the equation on the graph below to show you how I got my answer.
If this answer is correct, please make me Brainliest!
Answer:
a) 0.9959 = 99.59% probability that the mean weight is less than 9.3 ounces
b) 0.0129 = 1.29% probability that the mean weight is more than 9.0 ounces
Step-by-step explanation:
To solve this question, we need to understand the normal probability distribution and the central limit theorem.
Normal Probability Distribution:
Problems of normal distributions can be solved using the z-score formula.
In a set with mean and standard deviation
, the zscore of a measure X is given by:
The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.
Central Limit Theorem
The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean and standard deviation
, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean
and standard deviation
.
For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.
Mean of 8.0 ounces and a standard deviation of 1.1 ounces.
This means that
(a) If 5 potatoes are randomly selected, find the probability that the mean weight is less than 9.3 ounces?
means that
This probability is the pvalue of Z when X = 9.3. So
By the Central Limit Theorem
has a pvalue of 0.9959
0.9959 = 99.59% probability that the mean weight is less than 9.3 ounces
(b) If 6 potatoes are randomly selected, find the probability that the mean weight is more than 9.0 ounces?
means that
This probability is 1 subtracted by the pvalue of Z when X = 9. So
has a pvalue of 0.9871
1 - 0.9871 = 0.0129
0.0129 = 1.29% probability that the mean weight is more than 9.0 ounces