Study Unit 1 - Fundamentals Flashcards

1
Q

What is the main goal of social scientists?

A

Social scientists aim to study and understand the social world through scientific methods.

(Study guide pg 272)

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2
Q

What are variables in the context of social sciences research?

A

Variables are pieces of information that change (vary) from one person to another.

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3
Q

Define independent variable.

A

An independent variable, also known as explanatory or predictor variable, is a variable that we think is a cause.

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4
Q

Define dependent variable.

A

A dependent variable, also known as response or outcome variable, is a variable that we think is an effect.

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5
Q

What is the difference between observational and experimental research designs?

A

Observational studies measure both independent and dependent variables without manipulating any variable. Experimental studies, however, manipulate the independent variable while measuring the dependent variable.

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6
Q

What does a between-subjects design mean?

A

In a between-subjects design, each participant in the study is in only one condition or level of the independent variable.

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7
Q

What does a within-subjects design mean?

A

In a within-subjects design, participants experience all the conditions of the study and are measured on the dependent variable after each exposure.

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8
Q

What is operationalisation in research?

A

Operationalisation refers to the process of determining how variables will be manipulated or measured in a study.

(Study guide pg 32)

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9
Q

What is the meaning of reliability in the context of research measures?

A

Reliability refers to whether the measure repeatedly produces the same results under the same conditions.

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10
Q

What is the meaning of validity in the context of research measures?

A

Validity refers to whether the measure measures what it is supposed to measure.

(Study guide pg 32)

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11
Q

What are the four scales of measurement?

A

The four scales of measurement are nominal, ordinal, interval, and ratio.

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12
Q

Define nominal scale of measurement.

A

Variables with nominal scaling have different categories. There is no order or quantitative difference between the categories.

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13
Q

Define ordinal scale of measurement.

A

Variables with ordinal scaling have different categories arranged in an order or rank, although the difference between the categories cannot be quantified.

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14
Q

Define interval scale of measurement.

A

Variables with interval scaling have values on a numbered scale that are equally spaced. These equal intervals reflect equal differences in magnitude. However, the zero point on an interval scale is not meaningful.

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15
Q

Define ratio scale of measurement.

A

Variables with ratio scaling have the same characteristics as those with interval scaling with one difference—ratio scales have a meaningful, fixed zero point.

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16
Q

What is a population in research?

A

The population refers to the group of people researchers are interested to draw conclusions about.

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17
Q

What is a sample in research?

A

A sample is a subset of the population that researchers select and study, rather than studying an entire population.

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18
Q

What is the difference between probability sampling and non-probability sampling?

A

In probability sampling, each person in the population has a known probability of being sampled. In non-probability sampling, each person in the population has an unknown probability of being sampled.

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19
Q

What is the benefit of using probability sampling techniques?

A

Probability sampling techniques allow for statistical inference about the population from the sample data, i.e., the results obtained from the sample can be generalized to the population.

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20
Q

What is a disadvantage of non-probability sampling techniques?

A

Non-probability sampling techniques do not allow for statistical inference about the population, i.e., the results obtained from the sample may not be representative of the population.

21
Q

What is a frequency distribution?

A

A frequency distribution is an arrangement of data that classifies each measurement into categories or intervals and the number of times each measurement appears.

22
Q

What is a frequency table?

A

A frequency table is a method of representing the frequency distribution where individual values are listed from lowest to highest and their frequencies are tallied in a second column.

23
Q

How do you create a grouped frequency table?

A

A grouped frequency table is created by organizing values into class intervals or ranges of similar values, instead of listing each individual score.

24
Q

What is a histogram?

A

A histogram is a graphical representation of a frequency distribution in which rectangles are used to depict the frequencies of categories or intervals.

25
Q

What is a histogram?

A

A histogram is a graphical representation of a frequency distribution in which rectangles are used to depict the frequencies of categories or intervals.

26
Q

What is the difference between a bar graph and a histogram?

A

A bar graph represents distinct categories with bars that do not touch each other, while a histogram’s bars touch, representing grouped numerical data.

27
Q

What is the shape of a normal distribution?

A

A normal distribution follows a symmetrical bell-shaped curve, with a single peak in the center and two tails extending from it.

28
Q

What does it mean if a distribution is positively skewed?

A

A positively skewed distribution has more extremely small than large values, meaning the tail is towards the positive end of the x-axis.

29
Q

What does it mean if a distribution is negatively skewed?

A

A negatively skewed distribution has more extremely large than small values, meaning the tail is towards the negative end of the x-axis.

30
Q

What is a uniform distribution?

A

A uniform distribution is a distribution that has no peak and in which all outcomes are equally likely.

31
Q

What is a bimodal distribution?

A

A bimodal distribution is a distribution with two peaks, suggesting two different groups within the data set.

32
Q

What are the measures of central tendency?

A

The measures of central tendency are mean, median, and mode.

33
Q

How do you calculate the mean of a data set?

A

The mean is calculated by adding up all the values and dividing by the total number of values.

34
Q

What is the median of a data set?

A

The median is the middle value of an ordered data set, dividing it into two equal halves.

35
Q

What is the mode of a data set?

A

The mode is the value or values that appear most frequently in a data set.

36
Q

What does variability refer to in a data set?

A

Variability refers to the spread of the data, indicating how close or far apart the observations are from each other.

37
Q

What is the range of a data set?

A

The range is the difference between the highest and the lowest values in the data set.

38
Q

What is Standard Deviation?

A

Standard deviation is a measure of the spread in a distribution by taking into account the distance between every observation, Xi, and the mean, M, where the mean is a representative value of the observations in the data.

39
Q

What is the formula for Standard Deviation?

A

s = √(Σ((Xi - M)^2 )/(N-1))

40
Q

What is Variance?

A

Variance is a measure of spread that quantifies the average squared difference of each observation from the mean.

41
Q

What is the formula for Variance?

A

σ^2=Σ((Xi - M)^2)/(N-1)

42
Q

What is the difference between variance and standard deviation in terms of data distribution?

A

Variance is the average of the squared differences from the Mean, while standard deviation is the square root of the variance.

43
Q

Why is standard deviation more commonly used than variance?

A

Because standard deviation is expressed in the same units as the original data, whereas variance is expressed in squared units.

44
Q

What is Z-score?

A

Z-score is a standardized score that indicates how many standard deviations a data point is from the mean.

45
Q

What is the formula of Z-score?

A

Z = ((Xi – M) / s)

46
Q

How does Z-score help in comparing data?

A

Z-score allows comparisons within and between distributions by standardizing scores, thus providing context to raw scores, as it tells us how far an observation is from the mean, in terms of standard deviations.

47
Q

How is the range of a dataset calculated?

A

The range of a dataset is calculated by subtracting the smallest value in the dataset from the largest value.

48
Q

What is the standard deviation in a dataset?

A

The standard deviation is a measure of the spread of a dataset that takes into account the distance between every observation and the mean.

49
Q

Give examples of variables in the context of social sciences.

A

Examples are race, education level, income, or amount of time spent on social media.