Final Written exam - Week 5 Flashcards
(11 cards)
When critically appraising a research article, what are some key questions you should ask about the study design, sample size, and statistical methods used?
What type of study is it?
Is it a randomized controlled trial (RCT), cohort study, case-control study, cross-sectional, or qualitative?
Is the study design appropriate for the research question?
Does the design suit the objectives (e.g. RCT for testing efficacy)?
Was the study prospective or retrospective?
Prospective designs are usually more robust against bias.
Were controls used? Was randomization performed?
Randomization helps reduce selection bias; controls provide comparison.
Was blinding used (participants, researchers, assessors)?
Blinding helps reduce performance and detection bias.
Were ethical approvals obtained and participants consented?
Provide examples of categorical, numerical, and continuous data.
Categorical (Qualitative):
Nominal:
* Unordered categories. Can only calculate frequencies and percentages.
Ordinal:
* Ordered categories. Can calculate frequencies, percentages, medians.
Numerical (Quantitative):
Discrete: Countable values
Continuous:
* Values can fall along a continuum.
Briefly describe the three different sampling methods discussed in this lecture.
- Random sampling: Each member of the population has an equal chance of being selected.
- Stratified sampling: The population is divided into strata (e.g., age groups), and a random sample is taken from each stratum.
- Cluster sampling: The population is divided into clusters (e.g., geographic areas), and a random sample of clusters is selected. All members within the selected clusters are included in the sample.
What type of data are the mean, mode, and median best used for?
Mean: The average value, calculated by summing all values and dividing by the number of values. Sensitive to outliers.
Median: The middle value when the data are ordered from least to greatest. Less sensitive to outliers.
Mode: The most frequent value. Useful for categorical data and multimodal distributions.
- When to use each measure:
- Mean for symmetrical data
- median for skewed data or data with outliers
- mode for categorical data.
Describe box plots.
Summarize the distribution of numerical data, showing the median, quartiles (Q1 and Q3), and outliers. Useful for comparing distributions across different groups.
What is the purpose of a chi-square test?
Chi-square test:
* Used to analyze categorical data.
Define P - value.
P-value:
* The probability of observing the data (or more extreme data) if the null hypothesis is true.
Explain the purpose of a t-test. Under what circumstances would you use an independent samples t-test versus a paired samples t-test?
t-tests:
* Used to compare the means of two groups.
Independent samples t-test:
* Compares the means of two independent groups (e.g., treatment group vs. control group).
Paired samples t-test:
* Compares the means of two related groups (e.g., before and after measurements).
Explain the difference between variance and standard deviation.
Variance tells you how spread out the numbers are in a dataset.
Standard deviation is just the square root of the variance.
List and briefly describe some of the common statistical tests.
Goodness-of-fit test:
* Tests whether the observed frequencies of categories match expected frequencies.
Goodness-of-fit test:
* Tests whether the observed frequencies of categories match expected frequencies.
ANOVA (Analysis of Variance):
* Used to compare the means of more than two groups.
Correlation:
* Measures the linear relationship between two numerical variables.
Regression:
* Models the relationship between a dependent variable and one or more independent variables. Used to predict the value of the dependent variable based on the values of the independent variables.
Briefly describe the 3 factors impacting confidence intervals
- Sample size: Larger sample sizes lead to narrower intervals (more precise estimates).
- Variability: Greater variability in the data leads to wider intervals (less precise estimates).
- Confidence level: Higher confidence levels lead to wider intervals (greater certainty)
