In the context of and , why is a used more often than a when conducting studies?
Table of contents
- 1. Intro to Stats and Collecting Data1h 14m
- 2. Describing Data with Tables and Graphs1h 55m
- 3. Describing Data Numerically2h 5m
- 4. Probability2h 16m
- 5. Binomial Distribution & Discrete Random Variables3h 6m
- 6. Normal Distribution and Continuous Random Variables2h 11m
- 7. Sampling Distributions & Confidence Intervals: Mean3h 23m
- Sampling Distribution of the Sample Mean and Central Limit Theorem19m
- Distribution of Sample Mean - Excel23m
- Introduction to Confidence Intervals15m
- Confidence Intervals for Population Mean1h 18m
- Determining the Minimum Sample Size Required12m
- Finding Probabilities and T Critical Values - Excel28m
- Confidence Intervals for Population Means - Excel25m
- 8. Sampling Distributions & Confidence Intervals: Proportion1h 25m
- 9. Hypothesis Testing for One Sample3h 29m
- 10. Hypothesis Testing for Two Samples4h 50m
- Two Proportions1h 13m
- Two Proportions Hypothesis Test - Excel28m
- Two Means - Unknown, Unequal Variance1h 3m
- Two Means - Unknown Variances Hypothesis Test - Excel12m
- Two Means - Unknown, Equal Variance15m
- Two Means - Unknown, Equal Variances Hypothesis Test - Excel9m
- Two Means - Known Variance12m
- Two Means - Sigma Known Hypothesis Test - Excel21m
- Two Means - Matched Pairs (Dependent Samples)42m
- Matched Pairs Hypothesis Test - Excel12m
- 11. Correlation1h 24m
- 12. Regression1h 50m
- 13. Chi-Square Tests & Goodness of Fit2h 21m
- 14. ANOVA1h 57m
4. Probability
Basic Concepts of Probability
Struggling with Statistics?
Join thousands of students who trust us to help them ace their exams!Watch the first videoMultiple Choice
Which of the following best describes the difference between and in probability?
A
is always greater than for any dataset.
B
is the total number of occurrences of all events, while is the frequency of a single event.
C
is the proportion of times an event occurs out of the total number of trials, while is the sum of frequencies for all values up to and including a certain value.
D
and are two terms for the same concept in probability.
Verified step by step guidance1
Step 1: Understand the definition of relative frequency. Relative frequency is the ratio of the number of times a specific event occurs to the total number of trials or observations. It is calculated as \(\text{Relative Frequency} = \frac{\text{Frequency of a specific event}}{\text{Total number of observations}}\).
Step 2: Understand the definition of cumulative frequency. Cumulative frequency is the running total of frequencies up to and including a certain value or category. It sums the frequencies of all events or values less than or equal to a particular point.
Step 3: Recognize that relative frequency focuses on the proportion of a single event relative to the whole dataset, while cumulative frequency aggregates frequencies from the start of the dataset up to a certain event or value.
Step 4: Compare the two concepts: relative frequency gives insight into the likelihood of a single event, whereas cumulative frequency helps understand the accumulation or distribution of data up to a point.
Step 5: Conclude that the correct description is that relative frequency is the proportion of times an event occurs out of the total number of trials, while cumulative frequency is the sum of frequencies for all values up to and including a certain value.
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