MATH 225 Week 7 Assignment: Lab

Student Name

Chamberlain University

MATH-225 Statistical Reasoning for the Health Sciences

Prof. Name

Date

Sampling Methods

The sampling technique utilized for the Week 5 lab assignment to collect height data was convenience sampling. This non-random method involves selecting samples that are readily available or easy to access. While convenient, this approach may introduce bias because certain groups or outcomes might be overrepresented, reducing the generalizability of the findings. One major limitation of convenience sampling is that it does not fully capture the diversity of the entire population, which can result in systematic bias.

An alternative method that could have enhanced the representativeness of the data is systematic sampling. In systematic sampling, the researcher selects a random starting point and then collects every nth data point from the population. This method is considered a type of random sampling and tends to provide a more accurate reflection of the population characteristics, minimizing potential bias and increasing reliability.

Statistical Analysis

The summary of statistical findings from the height data collected is presented in Table 1:

Table 1
Summary of Height Data Statistics

A point estimate is an approximation of a population parameter, such as the mean or average, derived from sample data. In this study, the point estimate of the mean height is 66.1 inches, which provides a central value around which the actual population mean is likely to fall (Encyclopedia Britannica, 2019).

Confidence Intervals

Confidence intervals define a range of values within which the true population parameter is likely to exist. For the collected height data, the 95% confidence interval suggests that the mean height of employees at my workplace lies between 65.1 inches and 67.1 inches. This interpretation indicates a 95% probability that the true population mean falls within this range.

To evaluate a 99% confidence interval, the following statistics were obtained:

Table 2
99% Confidence Interval Statistics

The 99% confidence interval has a wider margin of error compared to the 95% interval, reflecting increased uncertainty. This broader range increases the likelihood that the true population mean is captured within the interval, whereas the 95% interval has a 5% chance of excluding the true mean.

References

Encyclopedia Britannica. (2019). Point estimate. Retrieved from https://www.britannica.com/topic/point-estimate