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2 years ago

2 1/3 x 4 4/5as a fraction

Mathematics

2 answers:

monitta2 years ago

4 0

Answer:

11 1/5

Step-by-step explanation:

2 1/3 × 4 4/5

=7/3 × 24/5

=56/5

=11 1/5

nadya68 [22]2 years ago

3 0

Answer:

Step-by-step explanation:

8 4/15

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2 years ago

Read 2 more answers

Eight trials are simulated. The results are shown in the table.

bezimeni [28]

Answer:

2.897

Step-by-step explanation:

Let us find the mean and variance for the sample first.

105 104 110 112

114 106 108 109

Mean = sum/8 = 108.5

Variance = 12

Std dev = sq rt of variance = 3.464

Std error = std dev/ sq rt n

since n =8, we get std error = 1.225

Since sample size is small, df =8-1 =7

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Margin of error = std error x t critical = 1.225(2.365)

=2.897

3 0

2 years ago

A normally distributed random variable with mean 4.5 and standard deviation 7.6 is sampled to get two independent values, X1 and

mr Goodwill [35]

Answer:

Bias for the estimator = -0.56

Mean Square Error for the estimator = 6.6311

Step-by-step explanation:

Given - A normally distributed random variable with mean 4.5 and standard deviation 7.6 is sampled to get two independent values, X1 and X2. The mean is estimated using the formula (3X1 + 4X2)/8.

To find - Determine the bias and the mean squared error for this estimator of the mean.

Proof -

Let us denote

X be a random variable such that X ~ N(mean = 4.5, SD = 7.6)

Now,

An estimate of mean, μ is suggested as

$\mu = \frac{3X_{1} + 4X_{2} }{8}$

Now

Bias for the estimator = E(μ bar) - μ

= $E( \frac{3X_{1} + 4X_{2} }{8}) - 4.5$

= $\frac{3E(X_{1}) + 4E(X_{2})}{8} - 4.5$

= $\frac{3(4.5) + 4(4.5)}{8} - 4.5$

= $\frac{13.5 + 18}{8} - 4.5$

= $\frac{31.5}{8} - 4.5$

= 3.9375 - 4.5

= - 0.5625 ≈ -0.56

∴ we get

Bias for the estimator = -0.56

Now,

Mean Square Error for the estimator = E[(μ bar - μ)²]

= Var(μ bar) + [Bias(μ bar, μ)]²

= $Var( \frac{3X_{1} + 4X_{2} }{8}) + 0.3136$

= $\frac{1}{64} Var( {3X_{1} + 4X_{2} }) + 0.3136$

= $\frac{1}{64} ( [{3Var(X_{1}) + 4Var(X_{2})] }) + 0.3136$

= $\frac{1}{64} [{3(57.76) + 4(57.76)}] } + 0.3136$

= $\frac{1}{64} [7(57.76)}] } + 0.3136$

= $\frac{1}{64} [404.32] } + 0.3136$

= $6.3175 + 0.3136$

= 6.6311

∴ we get

Mean Square Error for the estimator = 6.6311

6 0

3 years ago