Lab #1

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Purdue University *

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301

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Statistics

Date

Apr 3, 2024

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pdf

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Name: Lilyhan Liao TA name/ class time: Fang, Yaxin, Fridays at 1:30-2:20pm Lecturer Name: Christina Munson Lab 1: Sampling Methods/ Bias 1. SRS #1 1 2 3 4 5 Height 61.74 66.09 59.72 68.46 65.78 2. SRS #2 1 2 3 4 5 Height 66.97 63.97 67.46 67.13 62.89 SRS #3 1 2 3 4 5 Height 71.34 70.18 63.80 68.27 65.27 SRS #4 1 2 3 4 5 Height 66.25 74.11 68.94 66.45 73.16 Table 1: Height SRSs Means SRS #1 SRS #2 SRS #3 SRS #4 Mean: 64.358 65.692 67.772 69.782 3. Mean Height: 67.766

Statistics Height N Valid 150 Missing 0 Mean 67.7657 Median 68.3600 Std. Deviation 4.31766 Range 21.75 Minimum 56.01 Maximum 77.76 4. a) In your opinion, are the sample means in Table 1 similar to or different than the mean of the fictitious “population”? Was variability due to small sample size apparent? In Table 1, the sample means are mostly more different in comparison to the sample mean given for the fictious population. In Table 1, it is quite evident that there is more of a wider range in means. There was variability due to the small sample size. There was no variability in the big sample size. b) Explain how increasing the sample size would affect how the sample means compare to the mean of the fictitious “population”. In the beginning, because a smaller group was analyzed, a range of numbers of where the mean could be was given to us. When it comes to analyzing statistics, this can lead to giving us inaccurate results. Inaccuracy can prove to be fatal to a study’s success. Higher variability means the values are less consistent. On the other hand, the fictitious population gave us one mean only. Not a range. Lower variability means the values are more consistent which leads us to more accurate results. 5. The subjects in the data set answered a call for volunteers to participate in this study. Assuming every subject who volunteered has a recorded response for every variable, what type of bias could possibly result from this sampling design? One type of bias that could arise from this type of sampling design could be voluntary sample bias. When a study is voluntary, it is likely that most subjects have strong opinions. This can lead to partial truth such as leaving out representative groups.

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