Introduction to SPSS and Data Analysis

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Questions and Answers

What defines the median in a given data set?

  • The most frequently occurring value in the data set.
  • The value at which 50% of the cases fall above and below. (correct)
  • The average of all the values in the data set.
  • The highest value in the data set.

In the context of the provided IQ data, which value represents an outlier?

  • 115
  • 109
  • 140 (correct)
  • 128

Which of the following statements about mean and median is true for the given data?

  • The mean is always equal to the median.
  • The mean can be affected by outliers, while the median is not. (correct)
  • The median is influenced by extreme values, while the mean is not.
  • Both the mean and median are calculated in the same way.

Which of the following correctly describes the mode in statistical terms?

<p>The most common value in a data set. (D)</p> Signup and view all the answers

What is the relationship between the median and the interquartile range?

<p>The interquartile range measures the spread of the middle 50% of data around the median. (B)</p> Signup and view all the answers

Which type of data is characterized by attributes such as color and sex?

<p>Nominal Data (A)</p> Signup and view all the answers

What are measures of variation used for in descriptive statistics?

<p>To assess how much the data points differ from one another (A)</p> Signup and view all the answers

Which measure is least affected by outliers in a dataset?

<p>Median (A)</p> Signup and view all the answers

What type of quantitative data can take any value within a given range?

<p>Continuous Data (A)</p> Signup and view all the answers

What is the primary purpose of measures of central tendency?

<p>To provide a representative value for the entire dataset (C)</p> Signup and view all the answers

Which of the following is NOT a type of measure of central tendency?

<p>Standard Deviation (C)</p> Signup and view all the answers

Which type of data includes variables like arch length and fluoride concentration?

<p>Quantitative Data (C)</p> Signup and view all the answers

Percentiles, deciles, and quartiles are used to describe what aspect of a dataset?

<p>Relative standing (A)</p> Signup and view all the answers

What does SPSS stand for?

<p>Statistical Package for Social Sciences (A), Statistical Product and Service Solutions (B)</p> Signup and view all the answers

Which of the following defines a sample in statistical terms?

<p>A subset of the population for which data are collected (B)</p> Signup and view all the answers

Which of the following is NOT a level of measurement in data classification?

<p>Categorical (C)</p> Signup and view all the answers

In statistics, what does the term 'variables' refer to?

<p>Specific outcomes and characteristics of the study population (A)</p> Signup and view all the answers

Which statement best describes observations in research?

<p>They are individual data elements collected during a study. (D)</p> Signup and view all the answers

What is the primary purpose of using scales in data measurement?

<p>To quantify and arrange items for comparative analysis (D)</p> Signup and view all the answers

Which of the following best differentiates descriptive statistics from inferential statistics?

<p>Descriptive statistics describes and summarizes data, whereas inferential statistics generalizes findings to a larger population. (B)</p> Signup and view all the answers

How are subjects defined in the context of statistical analysis?

<p>The units on which characteristics are measured (D)</p> Signup and view all the answers

What is the mode of the combined IQ scores for Classes A & B?

<p>109 (C)</p> Signup and view all the answers

In what situation is the normality assumption essential for statistical testing?

<p>For small sample sizes (C)</p> Signup and view all the answers

Which of the following tests is NOT a statistical normality test?

<p>Mann-Whitney U test (D)</p> Signup and view all the answers

Which graphical method can be utilized to assess the normality of data?

<p>Box plots (C)</p> Signup and view all the answers

What is the significance of the Central Limit Theorem?

<p>It implies that the sum of random variables converges to a normal distribution under certain conditions (A)</p> Signup and view all the answers

When can a parametric test be used based on the central tendency of the data?

<p>Only when the mean represents the center of the distribution (D)</p> Signup and view all the answers

Which statement accurately describes the relationship between modes and parametric tests?

<p>Modes do not affect the choice of tests used for normally distributed data (C)</p> Signup and view all the answers

What is indicated by the need for normality tests before conducting parametric tests?

<p>The data distribution may violate assumptions necessary for accuracy (B)</p> Signup and view all the answers

Flashcards

Data

All the information we collect to answer a research question.

Variables

Characteristics or attributes that are measured or observed in a study.

Subjects

The individuals or units on which characteristics are measured.

Observations

Individual pieces of information collected about subjects.

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Population

The entire group of subjects that we're interested in studying.

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Sample

A smaller group of subjects selected from the population.

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Descriptive Statistics

Used to summarize and describe characteristics of a dataset.

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Inferential Statistics

Used to draw inferences or conclusions about a population based on sample data.

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Median

The middle value when a dataset is ranked in order, with 50% of the values above and 50% below it.

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Mode

The most common data point in a dataset.

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Outlier

A data point that falls significantly far away from the rest of the data.

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Interquartile Range

The difference between the first and third quartiles in a dataset, representing the spread of the middle 50% of the data.

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Mean

The sum of all values divided by the number of values in a dataset.

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Qualitative Data

Data based on qualities or attributes, like gender, color, or tooth type. It is categorized, not measured.

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Quantitative Data

Data collected through numerical measurements, like using calipers for arch length or fluoride levels.

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Discrete Data

Quantitative data that can only take whole numbers, like the number of decayed, missing, or filled teeth (DMF) in a person's mouth.

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Continuous Data

Quantitative data that can take any value within a range, including decimals, like measuring arch length.

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Measures of Variation

Summary statistics that measure how spread out or varied a dataset is. Examples include range, variance, and standard deviation.

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Central Limit Theorem

A statistical theorem stating that the sum of many independent random variables, when scaled appropriately, will tend to follow a normal distribution.

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Standard Normal Distribution

A specific type of normal distribution with a mean of 0 and a standard deviation of 1.

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Normality Tests

Tests for normality, determining if data fits the normal distribution pattern.

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Kolmogorov-Smirnov Test

This test compares the observed data distribution to the expected normal distribution.

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Shapiro-Wilk Test

This test evaluates the correlation between the observed data and the expected normal distribution.

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Q-Q Probability Plots

A graphical method for assessing normality, where data points are plotted against their expected normal distribution values.

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Study Notes

Statistical Workshop Series

  • Workshop 1 focuses on SPSS introduction, data, and its attributes.

SPSS Software

  • Originally stood for Statistical Package for the Social Sciences (SPSS) now known as Statistical Product and Service Solutions.

Data Terminology

  • Data: Information collected to answer questions.
  • Variables: Outcome, treatment, study characteristics.
  • Subjects: Units for measuring characteristics.
  • Observations: Data elements.
  • Population: All subjects of interest.
  • Sample: A subset of the population.

Descriptive vs Inferential Statistics

  • Descriptive statistics summarize data.
  • Inferential statistics draw conclusions from data.

Sample and Population

  • Population: All subjects of interest.
  • Sample: Subset of the population.
  • Descriptive measure of a population is called a parameter.
  • Descriptive measure of a sample is called a statistic.

Scales of Measurement

  • Nominal: Categories without order (e.g., gender).
  • Ordinal: Categories with order (e.g., pain levels).
  • Interval: Ordered categories with equal intervals (e.g., temperature).
  • Ratio: Ordered categories with equal intervals and a true zero point (e.g., height).
  • Data types: Qualitative (categorical) – Nominal, ordinal. Quantitative (numerical) – Discrete, continuous

Data

  • Qualitative: Attributes (e.g., sex, color).
  • Quantitative: Measurement (e.g., arch length, concentration).
    • Discrete: Fixed values (e.g., whole numbers).
    • Continuous: Any value within a range (e.g., decimal values).

Descriptive Statistics

  • Organize data: Tables and Graphs.
  • Summarize data: Measures of central tendency, Measures of location and Measures of variation.

Measures of Central Tendency

  • Mean, Median, Mode

Measures of Location

  • Percentiles, Deciles, and Quartiles

Measures of variation

  • Range, Variance, Standard Deviation, Standard Error.

Frequency Distribution

  • Shows the number of times each value appears.

Normal Distribution

  • Symmetrical bell-shaped curve.
  • Mean, Median and Mode are the same in a normal distribution.

Central Limit Theorem

  • The sum of independent identically distributed random variables converges to a standard normal distribution.
  • Valid if sample size is greater than 30 (n > 30).

Standard Normal Distribution - Z-distribution

  • Used to standardize values.
  • Empirical Rule (68-95-99.7 Rule):
    • 68% of data within one standard deviation.
    • 95% of data within two standard deviations.
    • 99.7% of data within three standard deviations.

Statistical Tests for Normality Checks

  • Kolmogorov-Smirnov test.
  • Shapiro-Wilk Test.
  • Q-Q plots
  • Box Plots

When to apply Parametric and Non-Parametric Tests

  • Based on the nature of the data (continuous, discrete, ordinal, nominal).
  • Data distribution (symmetrical, skewed).
  • Population sample size.
  • The mean and the median.

Non-parametric Tests

  • Chi-Square.
  • Wilcoxon signed rank.
  • Mann-Whitney U.
  • Kruskal Wallis.
  • Friedman ANOVA.
  • Spearman Rank correlation.

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