Introduction to Research Design, Research Ethics, Educational Statistics, and SPSS

Question 1

Accessible population

Answer 1

An “accessible population” is the smaller group of people or things that a researcher can easily study because they’re within reach and practical to include in a study. It’s the part of the bigger group that the researcher can actually work with.

Question 2

Alternate-form reliability

Answer 2

Checking if two different versions of a test give similar results.

Question 3

Cluster sampling

Answer 3

Picking groups of things to study instead of every single thing

Question 4

Concurrent validity

Answer 4

Checking if a new test agrees with an already trusted test.

Question 5

Construct validity

Answer 5

Making sure a test measures what it’s supposed to.

Question 6

Content validity

Answer 6

Checking if a test covers everything it’s supposed to.

Question 7

Continuous variable

Answer 7

Something you measure that can have any value.

Question 8

Cross-sectional study

Answer 8

Looking at a group at one point in time.

Question 9

Descriptive statistics

Answer 9

Numbers that describe things.

Question 10

Discrete variable

Answer 10

Something you count that can’t be in between whole numbers.

Question 11

Experimental study

Answer 11

A controlled study where you change something on purpose.

Question 12

Inferential statistics

Answer 12

Using data from a sample to make guesses about a larger group.

Question 13

Internal consistency

Answer 13

Checking if all parts of a test measure the same thing.

Question 14

Interval scale

Answer 14

Numbers with equal distances, but no true zero point.

Question 15

Longitudinal study

Answer 15

Following a group of people over time.

Question 16

Nominal scale

Answer 16

Naming or categorizing things without order.

Question 17

Observational study

Answer 17

Watching and studying things without changing them on purpose.

Question 18

Ordinal scale

Answer 18

Putting things in order, like 1st, 2nd, 3rd.

Question 19

Parameter

Answer 19

A number that tells something about a whole group.

Question 20

Population

Answer 20

All the people or things you’re interested in studying.

Question 21

Predictive validity

Answer 21

Seeing if a test can guess something in the future.

Question 22

Qualitative variable

Answer 22

Describing things without numbers.

Question 23

Quantitative variable

Answer 23

Something you measure that’s a number.

Question 24

Quasi-experimental study

Answer 24

Similar to an experiment but not completely controlled.

Question 25

Ratio scale

Answer 25

Numbers with a clear zero point and equal distances.

Question 26

Questionnaire

Answer 26

A list of questions to gather information.

Question 27

Research question

Answer 27

What you're trying to find out in your study.

Question 28

Sample

Answer 28

A smaller group of people or things you study to understand the bigger group.

Question 29

Simple random sample

Answer 29

Picking people or things randomly from a group.

Question 30

Statistic

Answer 30

A number that describes something about a sample

Question 31

Stratified sampling

Answer 31

Dividing a group into smaller groups and picking from each.

Question 32

Target population

Answer 32

The specific group you're trying to learn about.

Question 33

Test–retest reliability

Answer 33

Checking if a test gives consistent results when used again later.

Question 34

A researcher finds that students using a structured form of cooperative learning tend to do better than those using an unstructured form. The researcher concludes that the structured form is more effective. Which of the following research designs would typically provide the strongest support for such a conclusion? a. Observational. b. Quasi-experimental. c. Experimental.

Answer 34

c. Experimental.

Question 35

A teacher wants to summarize how well her students did on a social studies test, and is not interested in making conclusions about a larger population of students. What type of statistics is she likely to employ? a. Descriptive statistics. b. Inferential statistics.

Answer 35

a. Descriptive statistics.

Question 36

Double check this one

Answer 36

b. a parameter referred to as Ȳ The mean for a population is a parameter, not a statistic. In statistics, a "parameter" refers to a numerical value that describes a characteristic of a population. The mean is a measure of central tendency that represents the average value of all the data points in a population. On the other hand, a "statistic" is a numerical value that describes a characteristic of a sample, not the entire population.

Question 37

Double check this one

Answer 37

a. a statistic referred to as Ȳ The mean for a sample is a statistic and is often referred to as "Y-bar" or "Ȳ". A statistic is a numerical value that describes a characteristic of a sample, whereas a parameter refers to a numerical value that describes a characteristic of a population. In this case, the mean of a sample is a statistic because it represents the average value of the data points within the sample, not the entire population.

Question 38

Suppose we are interested in making inferences about third-grade writing achievement in Florida based on the writing scores of a subgroup of students who participated in the study. The subgroup who participated is referred to as the a. sample b. population c. sample population.

Answer 38

a. sample In this scenario, the subgroup of students who participated in the study and whose writing scores are being used to make inferences about third-grade writing achievement in Florida is referred to as the "sample." The term "sample" refers to a smaller subset of the population that is studied to draw conclusions about the larger population.

Question 39

Suppose we are interested in making inferences about third-grade writing achievement in Florida based on the writing scores of a subgroup of students who participated in the study. The third-graders in Florida about whom we wish to make inferences are referred to as the a. sample b. population c. sample population

Answer 39

b. population In this scenario, the third-grade students in Florida about whom you wish to make inferences regarding their writing achievement represent the larger group of interest. This larger group is referred to as the "population." The "population" encompasses all the individuals or units that you want to draw conclusions about. The subgroup of students who participated in the study (the sample) is used to make inferences about the larger population.

Question 40

When all possible subsets have an equal chance of becoming the sample, the sample is referred to as a a. convenience sample b. deliberate sample c. simple random sample d. cluster sample.

Answer 40

c. simple random sample When all possible subsets of the population have an equal chance of being selected as the sample, it is referred to as a "simple random sample." This sampling method ensures that every member of the population has an equal probability of being included in the sample, which helps to minimize bias and ensure that the sample is representative of the larger population.

Question 41

Suppose participants in a study indicate their ethnicity, and the different ethnicities are assigned numerals (e.g., Hispanic = 1, White = 2, Black = 3, Asian = 4). Ethnicity has been measured on which scale of measurement? a. Nominal. b. Ordinal. c. Interval. d. Ratio.

Answer 41

a. Nominal In this scenario, ethnicity has been measured using a nominal scale of measurement. The nominal scale is the lowest level of measurement and involves categorizing data into distinct categories or groups without any inherent order or ranking. Assigning numerals to different ethnicities without implying any meaningful order or ranking indicates the use of a nominal scale.

Question 42

If a researcher reports Cronbach’s alpha, she is reporting an estimate of the a. test–retest reliability b. internal consistency reliability c. content validity d. criterion-related validity.

Answer 42

b. internal consistency reliability When a researcher reports Cronbach's alpha, they are providing an estimate of the internal consistency reliability of a measurement instrument, such as a questionnaire or a test. Internal consistency reliability assesses how closely related the items within a measurement instrument are to each other, indicating how consistently they measure the same underlying construct.

Question 43

If a researcher presents evidence about how well the sample of items on a test represents the domain of items, the researcher is documenting a. test–retest reliability b. internal consistency reliability c. content validity d. criterion-related validity.

Answer 43

c. content validity When a researcher presents evidence about how well the sample of items on a test represents the domain of items it is intended to measure, the researcher is documenting content validity. Content validity is concerned with the extent to which the items in a measurement instrument (such as a test or questionnaire) adequately cover the full range of content or construct being measured. It assesses whether the items are relevant and comprehensive in representing the construct of interest.

Question 44

Extraneous Variable

Answer 44

Something that researchers try to control or account for in an experiment because it could potentially influence the results of the study.

Question 45

Confounding Variable

Answer 45

A confounding variable is a specific type of extraneous variable that is actually related to both the independent and dependent variables. It messes up the cause-and-effect relationship between the independent and dependent variables because it introduces a third variable that affects the results. If a confounding variable is present and not properly controlled, it can make it seem like the independent variable is causing an effect when it's actually the confounding variable causing the change.

Question 46

What are the four major types of quantitative research design?

Answer 46

True Experimental Quasi-Experimental Correlational Causal Comparative

Question 47

Which quantitative research design type has the highest internal validity?

Answer 47

True Experimental

Question 48

Which quantitative research design type requires a higher complexity of statistical analysis?

Answer 48

Casual Comparative

Question 49

If I have a study design in which I manipulate the independent variable but do not randomly assign a unit of analysis, what quantitative research design am I utilizing?

Answer 49

Quasi-experimental research design Quasi-experimental designs resemble true experiments in that they involve manipulation of an independent variable to observe its effects on a dependent variable. However, they lack full randomization of participants or subjects into different groups, which is a key feature of true experimental designs. Quasi-experimental designs are often used when random assignment is difficult or unethical, but researchers still want to examine the effects of an independent variable. While they can provide valuable insights, it's important to be cautious when interpreting the results of quasi-experiments due to the potential for confounding variables and other limitations.

Question 50

If I have a study design in which I manipulate the independent variable and have a randomly assign a unit of analysis, what quantitative research design am I utilizing?

Answer 50

True experimental research design In a true experimental design, researchers manipulate an independent variable to observe its impact on a dependent variable while also using random assignment to allocate participants or subjects to different groups. Random assignment is a key feature of true experiments because it helps ensure that the groups being compared are equivalent at the start of the experiment. This minimizes the influence of extraneous variables and increases the likelihood that any observed differences in the dependent variable are due to the manipulation of the independent variable

Question 51

If I have a study design in which I do not manipulate the independent variable and have a continuous independent variable, what quantitative research design am I utilizing?

Answer 51

Correlational research design. In a correlational research design, the goal is to examine the relationship between two or more variables without manipulating them. Instead of controlling variables and establishing cause-and-effect relationships, correlational studies focus on measuring the extent to which changes in one variable are associated with changes in another variable.

Question 52

If I have a study design in which I do not manipulate the independent variable and do not have a continuous independent variable, what quantitative research design am I utilizing?

Answer 52

Causal-comparative or "ex post facto" explores possible cause-and-effect relationships by examining existing differences between groups without manipulating the independent variable. In other words, it's a way to investigate the potential effects of an independent variable that cannot be directly manipulated for ethical or practical reasons.

Question 53

14 healthy females, age 25, volunteered for the study. 7 participants were randomly assigned to wear compression stockings on the lower legs and 7 students were randomly assigned to wear traditional cotton socks. After a 10k run all participants were asked to rate muscle soreness on a scale from 1 (no soreness) to 10 (extreme soreness). What type of quantitative design is this? 1. Quasi-experiment 2. True experiment 3. Causal Comparative 4. Correlational

Answer 53

True experiment. Here's why: There is manipulation of the independent variable: The researchers manipulated the type of socks worn (compression stockings vs. traditional cotton socks). This manipulation is a hallmark of true experiments. Random assignment: Participants were randomly assigned to wear either compression stockings or traditional cotton socks. Random assignment helps create comparable groups at the beginning of the experiment, reducing the likelihood of confounding variables affecting the results. Cause-and-effect relationship: By manipulating the independent variable (type of socks worn) and randomly assigning participants, the researchers are attempting to establish a cause-and-effect relationship between the independent variable and the dependent variable (muscle soreness after a 10k run). In summary, the study involves manipulation, random assignment, and aims to establish a cause-and-effect relationship, all of which are characteristics of a true experimental design.

Question 54

Mindfulness, Stress Coping and Everyday Resilience among Emerging Youth in a University Setting A two-group pre-test post-test experimental design was used to assess the effectiveness of the mindfulness curriculum on students’ coping strategies. The treatment group consisted of students in the mindfulness communication freshman seminar. The control condition consisted of students enrolled in a standard introductory communication course taught by the same instructor. Both courses included regular class lectures, small group discussions, in-class exercises, homework and exams. The pre-test and post-test questionnaires, administered in both groups during the first and last weeks of the semester. What type of quantitative design is this? 1. Quasi-experiment 2. True experiment 3. Causal Comparative 4. Correlational

Answer 54

Quasi-experiment. Here's why: The study involves manipulation of an independent variable (mindfulness curriculum) to assess its effectiveness on students' coping strategies. However, it's considered quasi-experimental because participants are not randomly assigned to groups. The treatment group receives the mindfulness curriculum, while the control group receives a standard introductory communication course. The groups are not randomly assigned, which is a key feature of true experiments. Instead, they are pre-existing groups based on the courses they are enrolled in. Since participants are not randomly assigned to groups, the researchers have less control over potential confounding variables that could affect the results. This is a common characteristic of quasi-experimental designs. The study assesses the impact of the mindfulness curriculum by comparing pre-test and post-test scores within each group. While this design allows for the exploration of cause-and-effect relationships, it lacks the level of control achieved through random assignment in true experiments. In summary, the study incorporates elements of experimentation by manipulating the independent variable and assessing its effects, but due to the absence of random assignment, it is categorized as a quasi-experimental design.

Question 55

Player positions: Anthropometric and Physical Fitness in Elite Rugby (comparisons of backs and forwards on weight, speed, agility, power, and aerobic fitness) Type of Quantitative Design? 1. True Experiment 2. Quasi-experiment 3. Causal Comparative 4. Correlational

Answer 55

Causal Comparative. Here's why: The study aims to compare two distinct groups (backs and forwards) in terms of various variables (weight, speed, agility, power, and aerobic fitness). The comparison between these groups is the focus of the study. There is no manipulation of an independent variable, which is a key aspect of true experiments. Instead, the researchers are observing and comparing existing groups based on their player positions. The term "causal comparative" suggests that the study aims to explore possible causal relationships by comparing groups that have already been defined by their characteristics (in this case, player positions). The researchers are investigating if the observed differences in variables might be caused by the participants' positions (backs vs. forwards). This design doesn't involve random assignment, and the researchers are not manipulating variables. Instead, they are examining potential causal relationships between pre-existing groups. In summary, the study's main focus is on comparing existing groups (backs and forwards) based on various variables. Since there is no manipulation of an independent variable and the study aims to explore causal relationships through this comparison, it is categorized as a causal comparative design.