Use the quadratic formula to solve x2 – 3x - 2 = 0.
2 answers:
Answer:
2.5 or 3.5
Step-by-step explanation:
The quadratic formula is .
a, b, and c are determined by the terms in the formula ax^2 + bx + c
They gave you the equation x^2 - 3x - 2, which fits that formula. a is 1, b is -3, and c is -2. So plug those values into the equation:
So x is 3 plus or minus -1/2. 3 plus -1/2 is 2.5
3 minus -1/2 is 3.5
So the 2 possible x values are 2.5 and 3.5.
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Answer:
The length of the line segment UV is 76 units
Step-by-step explanation:
In a triangle, the line segment joining the mid-points of two sides is parallel to the third side and equal to half its length
In Δ ONT
∵ U is the mid-point of ON
∵ V is the mid-point of TN
→ That means UV is joining the mid-points of two sides
∴ UV // OT
∴ UV = OT
∵ UV = 7x - 8
∵ OT = 12x + 8
∴ 7x - 8 = (12x + 8)
→ Multiply the bracket by
∵ (12x + 8) =
(12x) +
(8) = 6x + 4
∴ 7x - 8 = 6x + 4
→ Add 8 to both sides
∴ 7x - 8 + 8 = 6x + 4 + 8
∴ 7x = 6x + 12
→ Subtract 6x from both sides
∴ 7x - 6x = 6x - 6x + 12
∴ x = 12
→ Substitute the value of x in the expression of UV to find it
∵ UV = 7(12) - 8 = 84 - 8
∴ UV = 76
∴ The length of the line segment UV is 76 units
Answer:
Let X the random variable that represent the number of children per fammili of a population, and for this case we know the following info:
Where and
We select a sample of n =64 >30 and we can apply the central limit theorem. From the central limit theorem we know that the distribution for the sample mean is given by:
And for this case the standard error would be:
Step-by-step explanation:
Previous concepts
Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".
The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".
The central limit theorem states that "if we have a population with mean μ and standard deviation σ and take sufficiently large random samples from the population with replacement, then the distribution of the sample means will be approximately normally distributed. This will hold true regardless of whether the source population is normal or skewed, provided the sample size is sufficiently large".
Solution to the problem
Let X the random variable that represent the number of children per fammili of a population, and for this case we know the following info:
Where and
We select a sample of n =64 >30 and we can apply the central limit theorem. From the central limit theorem we know that the distribution for the sample mean is given by:
And for this case the standard error would be: