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Lecture

# STAT 151 (09/16/13) Ch 5&6

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School
University of Alberta
Department
Statistics
Course
STAT151
Professor
Paul Cartledge
Semester
Fall

Description
STAT 151 (September 16, 2013) Chapter 5 & 6 (w/ Sampling Type Overview) Sampling: Sampling frame – list created of subjects from a population chosen to be a part of the sample Random sample – sampling where each element of a population has a chance to be selected to be a part of the sample Other sampling methods: Stratified random sample: divided population into strata (SRS from each stratum) Elements (random sampling conducted on each strata) Cluster random sample: population divided into clusters and then random whole clusters are chosen Reduces cost by increase sampling efficiency Systematic sample: individuals are chosen from a sampling frame using a system Convenience sample: only individuals of a population who are conveniently available are chosen Voluntary response: individuals who volunteer their answer/responses to be collected (biased) Boxplots: - shows center spread, and skewness of a data (shows 2 layers of skewedness) EX Dataset: 7.9, 9.1, 9.2, 9.3, 9.4, 9.4, 9.5, 9.6, 9.6, 9.7 1. Rank the data smallest to largest. 2. Find median, Q1, Q3, and IQR a. According to ex: i. Q1: 9.2 ii. Q2: 9.6 iii. Median = 9.4 iv. IQR = 0.4 b. Find points beyond boundaries: 1.5*IQR below Q1 and 1.5*IQR above Q3 i. Aka lower and upper inner fence ii. These points are outliers (because it is outside the interquartile range) iii. If IQR = 0.4 1. Lower I.F. = 9.2-0.6 = 8.6 2. Upper I.F. = 9.6+0.6 = 10.2 iv. Marked with perpendicular dotted line 3. Find the smallest & largest values within the respective inner fences a. With the example = 9.1-9.7 4. Draw a linear scale containing ALL the data (even the ones not included within
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