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The completed table is given below,
the percentage of girls in the class is 47.62%,
the percentage of boys in the class is (100-47.62)% = 52.38%,
the percentage of students that love Math is 36.5%,
the percentage of students that love Reading is 22%, and
the percentage of students that love Science is 41.27%
To make comparison and statistical analysis easier, numerical data is systematically and logically represented in tabulations as rows and columns. Grouping relevant data together makes comparison easier and aids in statistical analysis and interpretation.
To put it another way, tabulation is the process of organizing data and presenting it in a tabular format. Depending on the type of categorization, it might be double, complicated, or simple.
The below table yields that
The total number of students is 315
The fraction of girls in the class is 150/315 = 0.4762
So, the percentage of girls in the class is 47.62%
Hence the percentage of boys in the class is (100-47.62)% = 52.38%
The fraction of students that love Math is 115/315 = 0.365
So, the percentage of students that love Math is 36.5%
The fraction of students that love Reading is 70/315 = 0.22
So, the percentage of students that love Reading is 22%
The fraction of students that love Science is 130/315 = 0.4127
So, the percentage of students that love Science is 41.27%
Learn more about tabulation here-
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Answer:
a. For n=25, the mean and standard deviation of the prices of the mobile homes all possible sample mean prices are $63,800 and $1,580, respectively.
b. For n=50, the mean and standard deviation of the prices of the mobile homes all possible sample mean prices are $63,800 and $1,117, respectively.
Step-by-step explanation:
In this case, for each sample size, we have a sampling distribution (a distribution for the population of sample means), with the following parameters:
For n=25 we have:
The spread of the sampling distribution is always smaller than the population spread of the individuals. The spread is smaller as the sample size increase.
This has the implication that is expected to have more precision in the estimation of the population mean when we use bigger samples than smaller ones.
If n=50, we have: