5 Samples are tested for the melting temperature of some polymer. The average of the samples was 150oCTest the hypothesis that the true mean value for all polymer is 155oC, assume the melting temperature is normally distributed with population standard deviation of 3o Use 95% confidence level.Test the hypothesis that the true mean value for all polymer is 155oC, assume the melting temperature is normally distributed with the sample’s standard deviation of 3o Use 95% confidence level.What is the required number of samples if we assume a sample standard deviation of 3oC, and tolerating a 1% error in the mean. Take µ=155oC, andα = 0.01.Another type of polymer was tested using 8 samples and the average was 152oC while the samples standard deviation was 2.5o Compared to the given data above and in Part 2, test the claim that the two types of polymers have the same average melting temperatures.Take α = 0.01.

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5 Samples are tested for the melting temperature of some polymer. The average of the samples was 150^oC

Test the hypothesis that the true mean value for all polymer is 155^oC, assume the melting temperature is normally distributed with population standard deviation of 3^o Use 95% confidence level.
Test the hypothesis that the true mean value for all polymer is 155^oC, assume the melting temperature is normally distributed with the sample’s standard deviation of 3^o Use 95% confidence level.
What is the required number of samples if we assume a sample standard deviation of 3^oC, and tolerating a 1% error in the mean. Take µ=155^oC, andα = 0.01.
Another type of polymer was tested using 8 samples and the average was 152^oC while the samples standard deviation was 2.5^o Compared to the given data above and in Part 2, test the claim that the two types of polymers have the same average melting temperatures.Take α = 0.01.

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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