Pysch Stats 1.2

What are the three scales of measurement used in this course?

Nominal, ordinal, and scale.

What does nominal measurement mean?

A measurement consisting of categories or names with no meaningful order.

What does ordinal measurement mean?

A measurement in which values have a meaningful ranking or order.

What does scale measurement mean in this course?

Numerical measurement in which the values represent meaningful quantitative differences; interval and ratio measurements are both treated as scale.

What is the key difference between nominal and ordinal measurement?

Nominal categories have no meaningful order, while ordinal categories can be meaningfully ranked.

What is the key difference between ordinal and scale measurement?

Ordinal measurement provides meaningful order but not necessarily meaningful numerical distances; scale measurement treats numerical differences as meaningful.

How does the course treat interval and ratio measurements?

Both are grouped together and called scale.

What characterizes an interval measurement?

Values are equally spaced, but there is no meaningful zero point, so multiplication and division are not meaningful.

What characterizes a ratio measurement?

Values are equally spaced and have a meaningful zero point, allowing meaningful multiplication and division.

How are Likert-style questions commonly treated in psychology?

They are often treated as interval measurements, especially when several related questions are averaged together.

Why is a university ranking an ordinal variable?

The rankings have a meaningful order, but the numerical gaps between ranks do not necessarily represent equal amounts of difference.

Why is a HAMA anxiety score treated as scale?

The HAMA produces a numerical score that represents quantitative differences in anxiety.

What measurement type is a yes/no variable?

Nominal.

Why does assigning numbers to categories not automatically make a variable scale?

The numbers may simply serve as labels for categories rather than representing meaningful quantities.

In the smell study, what was the independent variable?

Attentional load, with participants placed in high-load or low-load conditions.

In the smell study, what was the dependent variable?

Awareness of the coffee smell, measured by whether participants reported noticing it.

How was smell awareness measured in the smell study?

Participants answered whether they noticed a coffee smell with a yes/no response.

What measurement level was the smell-awareness dependent variable?

Nominal, because each participant was classified into a yes or no category.

What measurement level was the attentional-load independent variable?

Ordinal, because the conditions were high versus low attentional demand.

What made the smell study a true experiment?

The researchers manipulated attentional load and randomly assigned participants to conditions.

What was the population of interest in the smell study?

Adults with typically developing senses of smell.

What was an example of the sample in the smell study?

The participants who actually took part in the study, such as the 40 participants assigned to each condition.

What are descriptive statistics used for?

Organizing and summarizing a dataset using tools such as graphs and numerical summaries.

What are inferential statistics used for?

Drawing broader inferences from data using laws of chance and probability.

What is the key difference between descriptive and inferential statistics?

Descriptive statistics summarize the observed data, while inferential statistics use data to draw broader conclusions.

What is a frequency table used to show?

How often values or categories occur, often using counts and percentages.

What does a histogram show?

The distribution of scale-level numerical data, with each bar representing the number or percentage of observations at a score or score range.

How is a histogram organized?

Its values are arranged in numerical order.

What does each dot in a scatterplot represent?

Two variables measured for one person or case in the dataset.

What do bar graphs typically display in this presentation?

Aggregated data such as group means.

What are line graphs usually used to visualize?

Changes over time.

What is the main difference between raw and aggregated data?

Raw data show individual observations, while aggregated data summarize observations, such as with group means.

What information can box plots show?

The median, 25th percentile, 75th percentile, interquartile range, and potential outliers, along with group comparisons when applicable.

What is the interquartile range (IQR)?

The range containing the middle 50% of scores, extending from the 25th percentile to the 75th percentile.

What does the 25th percentile represent in a box plot?

The point below which approximately 25% of scores fall.

What does the 75th percentile represent in a box plot?

The point below which approximately 75% of scores fall, leaving approximately 25% above it.

What can violin plots display?

Group means or medians along with the distributions of the data.

Why are visualizations of raw data useful?

They help researchers see patterns, check data entry, evaluate assumptions of statistical tests, and identify unusual values or distributional characteristics.

What is a normal distribution?

A bell-shaped, unimodal, symmetrical distribution with relatively few observations in the extreme tails.

What are the tails of a distribution?

The areas at the extreme ends of the distribution.

What does positive skew mean?

The distribution has a tail extending toward positive or higher values.

What does negative skew mean?

The distribution has a tail extending toward negative or lower values.

How can you determine whether a distribution is positively or negatively skewed?

Look at the direction in which the longer tail extends; a high-value tail indicates positive skew and a low-value tail indicates negative skew.

What is an outlier?

An extreme score that is very high or very low compared with the other observations.

What are possible explanations for an outlier?

It could result from junk data such as incorrect data entry or misunderstanding instructions, or it could represent a genuinely unusual participant.

Why should researchers be cautious about removing outliers?

There is usually no foolproof way to determine whether an extreme value is erroneous or represents a real but unusual observation.

What is a bimodal distribution?

A distribution with two prominent peaks.

What is a multimodal distribution?

A distribution with multiple prominent peaks.

What is the difference between bimodal and multimodal?

Bimodal specifically has two prominent peaks, while multimodal refers more generally to multiple peaks.

What is the main purpose of visualizing a data distribution?

To make patterns in the data visible, including its shape, spread, skewness, multiple peaks, and unusual observations.

What does a graph of aggregated data hide compared with a graph of raw data?

It can hide individual differences and the underlying distribution because observations have been summarized.

Why can modern graphs combine raw and aggregated data?

Combining them allows researchers to see summary information such as means or medians while also seeing how individual observations are distributed.

What does the Challenger visualization relate to?

It shows the relationship between launch temperature and damage index, with a trend line and the projected temperature range for the morning of the launch.

What does the trend line in the Challenger visualization show?

The overall relationship or trend between temperature at launch and damage index.

What is the central lesson of the Challenger graph example?

Data visualization can make important patterns and relationships easier to see by connecting numerical evidence with relevant context.