Podcast
Questions and Answers
What statistical test is used to measure the relationship between two continuous variables?
What statistical test is used to measure the relationship between two continuous variables?
- T-test
- Chi-Square Test
- ANOVA
- Pearson Correlation (correct)
In hypothesis testing with a p-value, when do you reject the null hypothesis?
In hypothesis testing with a p-value, when do you reject the null hypothesis?
- When the p-value is less than the significance level (α) (correct)
- When the p-value is equal to the significance level (α)
- When the p-value is a large positive number
- When the p-value is greater than the significance level (α)
What type of variables are examined using a Chi-Square test?
What type of variables are examined using a Chi-Square test?
- Ordinal variables
- Interval variables
- Continuous variables
- Categorical variables (correct)
In the example of 'Family Structure and Academic Performance,' what type of variable is 'Family Structure'?
In the example of 'Family Structure and Academic Performance,' what type of variable is 'Family Structure'?
In the context of Pearson correlation, which of the following best describes the 'strength' of a linear relationship?
In the context of Pearson correlation, which of the following best describes the 'strength' of a linear relationship?
What is the primary purpose of descriptive statistics?
What is the primary purpose of descriptive statistics?
Which of the following is an example of descriptive statistics?
Which of the following is an example of descriptive statistics?
What is the focus of inferential statistics?
What is the focus of inferential statistics?
Which statistical test is used to compare two groups of data from one population?
Which statistical test is used to compare two groups of data from one population?
Which test would be appropriate, if you want to know the effect of something before and after treatment?
Which test would be appropriate, if you want to know the effect of something before and after treatment?
If the p-value is less than the significance level (alpha), what decision should be made regarding the null hypothesis?
If the p-value is less than the significance level (alpha), what decision should be made regarding the null hypothesis?
Which statistical test is used to compare data from three or more groups?
Which statistical test is used to compare data from three or more groups?
In an independent samples t-test, what is being compared?
In an independent samples t-test, what is being compared?
Flashcards
eHealth Literacy
eHealth Literacy
The ability to seek, understand, and use health information from electronic sources.
Pearson Correlation
Pearson Correlation
A statistical measure assessing the strength and direction of the linear relationship between two continuous variables.
Chi-Square Test
Chi-Square Test
A statistical test used to determine if there is a significant association between two categorical variables.
Null Hypothesis
Null Hypothesis
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Significance Level (α)
Significance Level (α)
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Statistics
Statistics
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Descriptive Statistics
Descriptive Statistics
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Inferential Statistics
Inferential Statistics
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Mean
Mean
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Dependent Sample T-Test
Dependent Sample T-Test
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Independent Sample T-Test
Independent Sample T-Test
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Analysis of Variance (ANOVA)
Analysis of Variance (ANOVA)
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Parametric Tests
Parametric Tests
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Study Notes
Basic Statistics
- Statistics is a mathematical science focused on collecting, organizing, and analyzing data to draw meaningful conclusions.
Two Categories of Statistics
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Descriptive Statistics: Summarize and describe a large dataset in a clear, concise, and informative manner. Examples include mean, median, mode, range, standard deviation, and variance.
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Inferential Statistics: Aims to make generalizations about a larger dataset based on a smaller sample. Techniques include parametric tests like T-tests and ANOVA, correlation, and more.
Descriptive Statistics
- Mean: The average of a dataset.
- Median: The middle value in a sorted dataset.
- Mode: The most frequent value in a dataset.
- Range: The difference between the maximum and minimum values.
- Standard Deviation: A measure of the data's dispersion from the mean.
- Variance: The average of the squared differences from the mean.
Inferential Statistics
- Parametric Tests: T-tests, ANOVA (Analysis of Variance)
- Correlation: Measures the relationship between two continuous variables (e.g., Pearson correlation).
Likert Scale Interpretation
- Strongly Disagree: 1.00 - 1.80
- Disagree: 1.81 - 2.60
- Neutral/Uncertain: 2.61 - 3.40
- Agree: 3.41 - 4.20
- Strongly Agree: 4.21 - 5.00
Data Assumptions for Parametric Analysis
- Parametric tests require data to meet certain assumptions (normality, absence of outliers) for valid results.
Dependent Sample T-test
- Used to compare two different groups from a single population, to see if there's a significant difference between those groups.
Independent Sample T-test
- Used to compare data from two different groups to see if there's a significant difference between them.
Analysis of Variance (ANOVA)
- Used to compare three or more groups, to see if there's a significant difference between them.
Pearson Correlation
- Measures the strength and direction of a linear relationship between two continuous variables. Values range from -1.00 to 1.00; 0 represents no linear relationship.
Chi-Square Test
- Used to determine association between two categorical variables.
Research Questions
- Demographic Profile: Age, sex, and general average during Grade 11 of respondents.
- Academic Procrastination: Levels of academic procrastination for Grade 12 STEM students related to deadlines, assignments/activities, and upcoming exams.
- Procrastination & Gender: Any differences in academic procrastination levels related to gender (male/female).
- Correlation of Procrastination & Performance: A correlation between academic procrastination and academic performance.
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Description
Explore the basics of statistics, focusing on the differences between descriptive and inferential statistics. Learn about key descriptive measures such as mean, median, mode, range and standard deviation. Also, get an overview of inferential statistics and parametric tests.
