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In the June 1986 issue of Consumer Reports, some data on the calorie content of beef hot dogs is given. Here are the numbers of calories in 20 different hot dog brands:

186,181,176,149,184,190,158,139,175,148,

152,111,141,153,190,157,131,149,135,132.

Assume that these numbers are the observed values from a random sample of twenty independent standard random variables with meanμand variance \({{\bf{\sigma }}^{\bf{2}}}\), both unknown. Find a 90% confidence interval for the mean number of caloriesμ.

Short Answer

Expert verified

The 90% confidence interval for the mean number of calories is(148.09,165.60)

Step by step solution

01

Given information

There is a calorie content dataset of beef hot dogs. The dataset provides the number of calories in 20 different hot dog brands. The dataset is,

The numbers of calories are observed from a random sample of 20 independent normal random variables with mean \(\mu \) and variance \({\sigma ^2}\).

02

Determine some values from the data

Consider the sample mean \({\bar X_n} = \frac{1}{{20}}\sum\nolimits_{i = 1}^{20} {{X_i}} = 156.85\)

Now the standard deviation is\(\sigma ' = \frac{1}{{19}}\sum\nolimits_{i = 1}^{20} {\left( {{X_i} - {{\bar X}_n}} \right) = 22.64} \)

Now \(T_{19}^{ - 1}\left( {\frac{{1 + 0.90}}{2}} \right) = 1.729\)

03

Calculate the confidence interval

As there is said that the variance is unknown, so the confidence interval is,

\(\left( {{{\bar X}_n} - T_{n - 1}^{ - 1}\left( {\frac{{1 + \gamma }}{2}} \right)\frac{{\sigma '}}{{\sqrt n }},{{\bar X}_n} + T_{n - 1}^{ - 1}\left( {\frac{{1 + \gamma }}{2}} \right)\frac{{\sigma '}}{{\sqrt n }}} \right) = \left( {148.09,165.60} \right)\)

Therefore, we can conclude that with 90% confidence, the mean calories in a hot dog are between 148.09 and 165.60.

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Most popular questions from this chapter

Suppose that a random sample of eight observations is taken from the normal distribution with unknown meanμand unknown variance\({{\bf{\sigma }}^{\bf{2}}}\), and that the observed values are 3.1, 3.5, 2.6, 3.4, 3.8, 3.0, 2.9, and 2.2. Find the shortest confidence interval forμwith each of the following three confidence coefficients:

  1. 0.90
  2. 0.95
  3. 0.99.

Prove that the distribution of\({\hat \sigma _0}^2\)in Examples 8.2.1and 8.2.2 is the gamma distribution with parameters\(\frac{n}{2}\)and\(\frac{n}{{2{\sigma ^2}}}\).

Consider again the conditions of Exercise 19, and let\({{\bf{\hat \beta }}_{\bf{n}}}\)n denote the M.L.E. of β.

a. Use the delta method to determine the asymptotic distribution of\(\frac{{\bf{1}}}{{{{{\bf{\hat \beta }}}_{\bf{n}}}}}\).

b. Show that\(\frac{{\bf{1}}}{{{{{\bf{\hat \beta }}}_{\bf{n}}}}}{\bf{ = }}{{\bf{\bar X}}_{\bf{n}}}\), and use the central limit theorem to determine the asymptotic distribution of\(\frac{{\bf{1}}}{{{{{\bf{\hat \beta }}}_{\bf{n}}}}}\).

Question: Prove the limit formula Eq. (8.4.6).

When the motion of a microscopic particle in a liquid or a gas is observed, it is seen that the motion is irregular because the particle frequently collides with other particles. The probability model for this motion, which is called Brownian motion,is as follows: A coordinate system is chosen in the liquid or gas. Suppose that the particle is at the origin of this coordinate system at timet=0, and let(X, Y, Z)denote the particle's coordinates at any timet >0. The random variablesX,Y, andZare i.i.d. Each has a normal distribution with mean 0 and variance\({\sigma ^2}t\). Find the probability that at timet=2, the particle will lie within a sphere whose centre is at the origin and whose radius is 4σ.

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