ESM 1090 Exam #1

In preparation for exam #1.

Research

Coming to know something using a scientific method, which is a systematic way of acquiring new knowledge.

Hypothesis

A prediction of the outcome of research

Scientific Method

A method of gaining knowledge through 1. Identifying a problem 2. Formulating hypotheses 3. Determining what information needs to be collected 4. Organizing the gathered information, then 5. Interpreting the results (Intro.)

Population

Consists of all members of the groups of interest to one’s research study.

Sample

A subset of a population

Categorical Variable

Nominal and Ordinal levels of measurements

Numerical Data

Interval and Ratio levels of measurements. These scales are expressed in numbers unlike categorical variables.

Scales of Measurements

Nominal, ordinal, interval, and ratio.

Variable

Any measurable factor that has an effect on a phenomenon or phenomena

Ordinal Variable

Participants ranked in order from low to high, but it does not indicate how much lower or higher one participant is in relation to another.

Ratio

Measure how much participants differ from each other. The scale has an absolute zero point on its scale.

Research (2)

Formal systematic application of the scientific method to the study of a problem.

The Goal of Research

To describe, explain, predict, and control situations involving human beings.

The Five Ways of Knowing

1. Sensory System 2. Agreement with others. 3. Consulting an expert. 4. Logic 5. Scientific Method

Steps of the Scientific Method

1. Recognize and identify a problem or a question. 2. Clarify a problem. 3. Determine the information needed and how to obtain it (Data collection). 4. Organize the information obtained (Data Analysis) 5. Interpret the results

Practical Problem

A question of interest that can be answered with data.

Theoretical Question

Idea or question that is too vague to collect specific data.

Research Study Outline

1. Introduction 2. Literature Review 3. Review Methodology 4. Results 5. Discussion/Conclusion

Limitations of Scientific Method

There is a chance for measurement error.

Data

Pieces of information you collect and use to examine your research top

Variable

Any measurable factor that affects a phenomenon or phenomena, must have at least two categories, placeholder that can assume any one of a range of values, and May be measured by instruments.

Structured Question

Participants choose from responses already provided.

Semi-Structured Question

Do not have pre-determined choices

Unstructured Question

Open-Ended Questions, General Questions, Broad

Categorical Data

Uses words

Nominal

Their values identify what category they fall under, but do not have a meaningful order

Ordinal

Variables that have two or more categories with clear and meaningful order to the categories. If expressed in numbers, between scores are not equal.

Continuous Data

Uses numbers

Quantitative

Information that can be measured with numbers

Interval

Variables have a numerical value and can be measured along a continuum with equal intervals, and the scale has a absolute zero. Zero indicates the absence of whatever that is being measured and means none in real life.

Steps of identifying the Type of Date

1. Is the variable Categorical (Words) or Continuous (Numbers)? 2. If Categorical data, is it Nominal or Ordinal (Order)? 3. If continuous data, is it Interval or Ratio?

Empirical Approach (Scientific Method)

Learning through direct observation

Sample

A smaller group that represents a larger population.

Measuring Instruments

Surveys, interviews, and tests.

Statistical Analysis

Organize and understand information

Subjects

People and animals being studied without permission

Participants

Those who agree to be part of a study

Respondents

People who fill out surveys

Examinees

Those who take tests

What are the two main types of quantitative studies?

Non-experimental and experimental

Correlational

Relationships between variables without manipulation

In experimental studies, what is the independent variable?

Treatments

In experimental studies, what is the dependent variable?

How participants respond

Which group receives treatment?

Experimental

Which group does not receive treatment?

Control

Program Evaluation (Empirical Research)

Effectiveness of a specific program for a particular group

Five Systematic Steps

1. Raise research questions 2. Predict outcomes through hypothesis 3. Determine what data are needed to answer research questions 4. Organize the gathered data or information 5. Interpret results

Variable

Anything that can be measured that has an effect of a phenemonon

Standard Deviation

A measure of variation

Two main types of statistical analysis

Descriptive and inferential statistics

Descriptive Statistics

Summarize and organize data to describe certain characteristics (the average)

Inferential Statistic

Make predictions about the population

Range

Shows the difference between the highest and lowest scores

Correlational Statistics

Analyzes relationships between two or more variables

Correlational Coefficient

Ranges from 0.00 (no relationship) to 1.00 or -1.00 (a perfect relationship)

When relationships are positive…

One increases as the other increases…

When relationships are negative

One increases while the other decreases

Margin of Error

Results might differ from the true population values

Which graph for Categorical data?

Bar Graph

Which graph for Continuous data?

Histogram, Frequency Polygon

Inferential Statistics

Make predictions about a larger population based on a sample

Descriptive Statistics

Frequencies, percentages, and proportions.

Frequency (F)

Number of participants or cases that share a particular characteristic.

N

Total number of participants in a study.

Percentage (%)

How many participants out of 100 share a particular trait.

To calculate percentage…

Divide the smaller number by the total and multiply by 100.

What should you include when reporting percentages and why?

Frequencies because percentages alone can be misleading.

Proportion

Represented as a fraction or decimal.

What is often preferred, proportions or percentages? Why?

Percentages because they are easier to interpret.

Frequency Distribution

How often each slope appears in a data set.

Frequency Polygon

A visual representation of a frequency distribution.

Normal Curve (Bell-Shaped)

Most values cluster around the average and fewer values appear at extremes.

Positively Skewed

The long tail extends to the right.

Negatively Skewed

The long tail extends to the left.

Averages are also known as?

Measures of central tendency.

What are the averages (measures of central tendencies)?

Mean, median, and mode.

Mean

It is the most commonly used average.

How do you calculate the mean?

Total the scores and divide the total by the number of scores.

The mean is…

Usually rounded and reported to two decimals.

Symbols for Mean

M, m, x bar

The balance point in distribution of scores.

Mean

Deviations

The distance of each score from the mean.

Deviations from the mean sum to…

Zero.

What is a drawback of deviations?

The mean is pulled in the direction of extreme scores.

The mean is always inappropriate when describing which type of distributions?

Highly skewed distributions.

For which data distribution should the mean be calculated and interpreted?

“Normal” distribution

The mean should be only used with which scales of measurement?

Interval and ratio.

Median

Middle point in a distribution.

In the median, how are the scores distributed?

Half of the scores in a given data are above and half are below.

When there is an even number of scores…

The median is the mean of the two middle numbers.

True or False: The median is affected by extreme scores.

False.

When is it appropriate to use the median in distributions?

Highly skewed distributions.

When should you NOT use the median?

Nominal data.

Mode

The most frequently occurring score or category.

The mode is often…

Used for Nominal Data.

True or False: Reporting an average may not be needed for nominal data.

True.

In Normal Distributions…

The mean, median, mode all have the same value.

In positively skewed distributions…

The mean is higher than the median.

In negatively skewed distributions…

The mean is lower than the median.