1. Intro to Stats and Collecting Data
Intro to Stats
1:30 minutesProblem 2.CRE.4d
Textbook Question
In Exercises 1–5, use the data listed in the margin, which are magnitudes (Richter scale) and depths (km) of earthquakes from Data Set 24 “Earthquakes” in Appendix B
[Image]
Data Type
d. Given that the listed earthquake depths are part of a larger collection of depths, do the data constitute a sample or a population?
Verified step by step guidance1
Step 1: Begin by understanding the definitions of 'sample' and 'population' in statistics. A population includes all members of a defined group, while a sample is a subset of the population selected for analysis.
Step 2: Examine the problem statement. It mentions that the listed earthquake depths are part of a larger collection of depths. This implies that the data provided does not include all earthquake depths but rather a subset of them.
Step 3: Consider the implications of the data being a subset. Since the data does not represent the entire collection of earthquake depths, it is classified as a sample.
Step 4: Reflect on the purpose of using a sample. Samples are often used in statistics to make inferences about the population without needing to analyze every member of the population.
Step 5: Conclude that the listed earthquake depths constitute a sample because they represent only a portion of the larger collection of earthquake depths.
Verified video answer for a similar problem:This video solution was recommended by our tutors as helpful for the problem above
Video duration:
1mWas this helpful?
Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Population vs. Sample
In statistics, a population refers to the entire group of individuals or observations that share a common characteristic, while a sample is a subset of that population selected for analysis. Understanding whether data constitutes a sample or a population is crucial for determining the appropriate statistical methods to apply and for making inferences about the larger group.
Recommended video:
05:11
Sampling Distribution of Sample Proportion
Descriptive Statistics
Descriptive statistics summarize and describe the main features of a dataset, providing simple summaries about the sample and the measures. This includes measures of central tendency (mean, median, mode) and measures of variability (range, variance, standard deviation), which help in understanding the characteristics of the data being analyzed.
Recommended video:
Guided course
05:53Parameters vs. Statistics
Inferential Statistics
Inferential statistics involve using a sample of data to make generalizations or predictions about a population. This branch of statistics employs various techniques, such as hypothesis testing and confidence intervals, to draw conclusions and assess the reliability of the results obtained from the sample data.
Recommended video:
Guided course
05:53Parameters vs. Statistics
2:13mWatch next
Master Introduction to Statistics Channel with a bite sized video explanation from Patrick
Start learning
