ou have a friend who needs your help with interpreting a statistical analysis. Your friend is starting out in a quality control job, and has some data involving weights of bags of a certain type of product. They wanted to test the null hypothesis that the true mean of bags of this type is 300 grams, against a two-sided alternative. Unfortunately, they are just starting out with R, and didn't quite understand the t.test command. They used the following command and found the following output. > t.test(bags) One Sample t-test data: bags t = 696.55, df = 39, p-value < 2.2e-16 alternative hypothesis: true mean is not equal to 0 95 percent confidence interval: 309.1159 310.9164 sample estimates: mean of x 310.0162 Without doing any calculations, help your friend out here. Explain to them what this output tells us about their desired test. (Suppose the weights are normally distributed, and that the sample of bags is a simple random sample from the population of interest.)
You have a friend who needs your help with interpreting a statistical analysis. Your friend is starting out in a quality control job, and has some data involving weights of bags of a certain type of product. They wanted to test the null hypothesis that the true
> t.test(bags)
One Sample t-test
data: bags
t = 696.55, df = 39, p-value < 2.2e-16
alternative hypothesis: true mean is not equal to 0
95 percent confidence interval:
309.1159 310.9164
sample estimates:
mean of x
310.0162
Without doing any calculations, help your friend out here. Explain to them what this output tells us about their desired test. (Suppose the weights are
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