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Questions and Answers
What is the formula to calculate the proportion of scores?
p = f/n
What is the formula for calculating percentage?
p(100) = f/n(100)
A bar graph organizes categories vertically on the y-axis.
True
Which of the following is one of the measures of central tendency?
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What is the middle score in a distribution called?
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What is the formula to find the mean?
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What is the mode?
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The distribution with one value having a larger frequency is called ______.
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A normal curve is symmetric and unimodal.
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What should the researcher conclude if p > .01 in a two-tailed test?
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What is a variable in psychological statistics?
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What is a raw score?
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Which of the following best describes descriptive statistics?
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What is the purpose of inferential statistics?
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A sample is a set of all individuals of interest in a particular study.
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What is the meaning of a sampling error?
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Which of the following is an example of a continuous variable?
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What does a dichotomous variable represent?
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What is the independent variable in an experiment?
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What is the purpose of a control condition in an experiment?
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The __________ is a design used to assess behavior changes before and after an event.
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Which statistical method involves measuring one or more variables for each individual?
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What does normally happen between the highest and lowest scores in a range?
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Study Notes
Data Visualization Techniques
- Column Chart: Represents categories with rectangles; height is proportional to values.
- Proportion: Measures the fraction of the total group related to each score; formula is p = f/n.
- Percentage: Expresses amount as a number out of 100; formula is p(100) = f/n(100).
- Bar Graph: Similar to column charts but categories are vertical on the y-axis.
- Line Graph: Connects data points with lines, displaying quantitative values over time intervals.
Grouped Frequency Table
- Displays the frequency of individuals within value intervals; each interval groups a range of values.
Descriptive Statistics
- Central Tendency: Measures typical or representative values, including mean, median, and mode.
- Mean (M): Arithmetic average calculated as the sum of scores divided by the number of scores.
- Median (Mdn): Middle score of ordered data; found by arranging scores and locating the central value.
- Mode: Most frequently occurring value in the dataset.
Characteristics of Data
- Weighted Mean: Considers weights assigned to observations for calculating a single average.
- Use of Mean: Common in quantitative research, ideal for normally distributed data and equal-interval variables.
Shapes of Frequency Distribution
- Unimodal Distribution: One value has a significantly higher frequency than others.
- Bimodal Distribution: Two values have approximately equal high frequencies.
- Multimodal Distribution: Two or more frequencies significantly higher than others.
- Normal Curve: Symmetrical, bell-shaped distribution observed widely in nature.
- Kurtosis: Describes how frequency distribution deviates from normal; includes leptokurtic (peaked), mesokurtic (normal), and platykurtic (flat).
Distribution Symmetry
- Symmetrical Distribution: Frequencies on either side of the central point mirror each other.
- Skewed Distribution: Imbalanced frequency distribution; assessed for normality with specific skewness and kurtosis thresholds.
Hypothesis Testing
- Directional Hypothesis: Predicts direction of differences between populations.
- One-Tailed Test: Regions for rejecting the null hypothesis are one-sided.
- Two-Tailed Test: Regions for rejection are split across both sides; used when not predicting a specific direction.
- Null Hypothesis (H0): States no significant effect; tested against alternative hypotheses.
Variables and Measurements
- Variable: Characteristic or condition subject to change.
- Value: Possible number or category a score can have.
- Score: An individual’s value on a variable.
- Population: All individuals of interest in a study; sample represents the population in research contexts.
- Sampling Error: Difference between sample statistic and population parameter that naturally occurs.
Types of Variables
- Discrete Variable: Indivisible categories, e.g., number of students.
- Continuous Variable: Infinite possible values exist between any two observed values.
- Dichotomous Variable: Takes only two possible values.### Levels of Measurement
- Scales of measurement classify the nature of variable information.
- Nominal: Categorical values (e.g., Sex, Nationality).
- Ordinal: Rank-order values (e.g., Highest Educational Attainment, Likert Scale).
- Interval: Equal-interval values without an absolute zero (e.g., Temperature, IQ).
- Ratio: Interval scale with a true zero, quantifiable differences (e.g., Time to task completion).
Data Structures
- One Group with One Variable: One or more variables measured per individual, utilizing descriptive statistics.
- One Group with Two Variables: One group measured for two variables, aiming to identify patterns and relationships.
- Comparing Two or More Groups: Different groups measured on a variable, applicable in experimental and non-experimental studies.
Research Methods
- Correlational Method: Observes relationships between two variables, but does not explain or establish cause-and-effect.
- Quasi-experimental Design: Resembles real experiments but lacks key elements like random assignment.
- Pretest/Posttest Design: Assesses behavior changes by measuring scores before and after an event.
- Experimental Method: Manipulates one variable while observing another to establish causality.
- Ex-Post Facto Study: Examines effects of pre-existing characteristics without manipulation.
Research Variables
- Independent Variable: Manipulated by the researcher, with at least two levels (treatment conditions).
- Dependent Variable: Measured to assess treatment effects.
- Control Condition: Subjects do not receive experimental treatment to serve as a baseline.
Descriptive Statistics
- Summarizes a group of scores to enhance understanding of data.
- Frequency Distribution: Organized table showing the number of individuals in each category.
- Frequency Table: Lists numbers of individuals/subjects with different values for a variable.
Data Presentation Methods
- Histogram: Bar graph of frequency distribution with values on the horizontal axis and frequencies as bar heights.
- Frequency Polygon: Continuous line representing frequencies based on histogram data.
Constructing Frequency Tables
- Determine range, class size, and class width.
- Ensure no overlapping intervals, sufficient classes for data, and equal width for all classes.
- Steps: List each possible value, mark each score, and organize the counts.
Example Study
- Researchers observed the impact of background noise on classroom performance with three conditions: calming music, aggressive music, and no music.
This study exemplifies the application of independent and dependent variables, and the manipulation of different levels of background noise.
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Description
Test your knowledge on basic statistics concepts such as proportion, percentage, central tendency, and mean. This quiz covers essential formulas and definitions that are fundamental to understanding data analysis. Perfect for introductory statistics courses or anyone looking to refresh their skills.
