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Phantasy [73]
3 years ago
15

3(8a - 5b) – 2(a + b); use a = 3 and b = 2

Mathematics
2 answers:
Reika [66]3 years ago
8 0

Answer:

32

Step-by-step explanation:

3(8(3)-5(2))-2((3)+(2))

3(24-10) -2(5)

3(14) -10

42-10

32

timama [110]3 years ago
8 0

\huge\text{Hey there!}

\huge\textsf{3(8a - 5b) - 2(a + b)}\\\\\huge\textsf{= 3(8(3) - 5(2)) - 2(3 + 2)}\\\\\huge\textsf{= 3(24 - 10) - 2(3 + 2)}\\\\\huge\textsf{= (3)(14) - 2(3 + 2)}\\\\\huge\textsf{= 42 - 2(3 + 2)}\\\\\huge\textsf{= 42 - 2(5)}\\\\\huge\textsf{= 42 - 10}\\\\\huge\textsf{= 32}}

\huge\boxed{\textsf{Answer: 32}}\huge\checkmark

\huge\text{Good luck on your assignment \& enjoy your day!}

~\huge\boxed{\frak{Amphitrite1040:)}}

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3 years ago
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Zielflug [23.3K]

Answer:

The interval (-0.0199, 0.0510) represents the region of values where the true difference (in population terms now) between the initial proportion of registered voters that favour candidate X and the proportion of registered voters that favour candidate X just before election can take on with a confidence level of 90%.

Step-by-step explanation:

Confidence Interval for the population proportion is basically an interval of range of values where the true population proportion can be found with a certain level of confidence. It is usually obtained from the sample.

p₁ represents the proportion of registered voters that favour candidate X in the initial poll, way before the election.

p₂ represents the proportion of registered voters that favour candidate X in the poll just before the election.

So, for this question the confidence interval for the true difference between the population proportion of registered voters that favour candidate X way before the elections and the population proportion that favour candidate X just before the election lies within (-0.0199, 0.0510) with a confidence interval of 90%.

Confidence interval is calculated mathematically as thus:

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Margin of Error is the width of the confidence interval about the difference in the two sample proportions.

It is given mathematically as,

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Critical value = 1.645 (obtained from the z-tables because the sample size is large enough to ignore that information about the population standard deviation isn't given and t-critical value approximates z-critical value)

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