Week 11: Statistical Analysis Flashcards

1
Q

What are descriptive statistics?

A

Categories (frequencies, histograms, bar graphs, pie charts) or continuous data (frequency distributions, standard deviation, percentile, mean, median, mode) that are typically univariate (incorporates one variable)

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2
Q

What is a measure of central tendency?

A

A summary measure that attempts to describe a whole set of data with a single value that represents the middle or centre of its distribution

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3
Q

What are the six different measures of central tendency?

A

-Mean
-Median
-Mode
-Range
-Percentage
-Percentile

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4
Q

What is the mode?

A

The value that appears the most number of times in a data set

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5
Q

What is the mean?

A

The average of all the numbers in a data set

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6
Q

What is the median?

A

The middle number in a list of numbers ordered from smallest to largest

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7
Q

What is the range?

A

The difference between the lowest value and the highest value

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8
Q

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

A

A histogram presents numerical data, or the frequency distribution of continuous data (ex. one bar is 1-5 years, the next is 6-10 years, the next 11-15 years, and so on)

A bar chart presents categorical data, or the frequency of discrete variables (ex. one bar is the population of town A, the next is the population of town B, and so on)

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9
Q

What is a normal distribution curve used to show?

A

How much of a population is within a given standard deviation of the mean in a set of continuous data; looks like a bell curve, where the greatest proportion of the population it at the mean (centre) and the smallest proportion are at either extreme of the standard deviation

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10
Q

What is meant by “skewness” when graphically depicting continuous data?

A

Skew occurs when the bell curve of a normal distribution is “pushed” to one side or the other

Negative skew: the mode is “pushed” to the right, meaning the “tail” (smaller proportions of the standard deviations) create a tail to the left

Positive skew: the mode is “pushed” to the left, meaning the “tail” (smaller proportions of the standard deviations) create a tail to the right

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11
Q

What are the two types of inrefential statistics?

A

-Bivariate (comparing two variables; usually dependent/independent)
-Multivariate (comparing 3+ variables; usually one independent and multiple dependent)

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12
Q

What are the steps for determining the appropriate statistical test for a set of data? (3)

A
  1. Write an alternative (“there will be an effect”) and a null (“there will be no effect”) hypothesis
  2. Determine whether you have parametric (normal distribution + large sample size + independence across participants/data) or non-parametric data
  3. Use the statistical analysis chart to select a specific statistical test
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13
Q

What is a t-test in statistical analysis?

A

Compares the means/distribution of the two groups; the dependent variable is continuous, so it is possible to graph the distribution curve of both independent variable groups on a t-chart to compare them

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14
Q

What is a chi-square chart in statistical analysis?

A

Used to compare frequencies (which appear as a number in each cell of the table/chart) (ex. frequency of IVa + DVa vs. IVb + DVa vs. IVb + DVa vs. IVb + DVb)

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15
Q

What is “Pearson’s correlation” in statistical analysis?

A

A statistical test which depicts the degree and direction of a relationship between continuous variables

Positive correlation (+) = ascending line; as one variable increases so does the other

Negative correlation (-) = descending line; as one variable increases the other decreases

Strong correlation = closer to 1

Weak correlation = closer to 0

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16
Q

What is meant by “statistical significance” in statistical analysis?

A

p = probability

A low p value (less than .05) means it is unlikely for a certain result to occur by chance

A high p value (greater than .05) means it is likely for a certain result to occur by chance

17
Q

When we determine a result to be statistically significant (greater than .05) during statistical analysis, what does that mean for our null and alternative hypothesis?

A

If statistical significance is greater than .05, there is a high probability that our results reflect a true phenomenon, therefore…
-We reject our null hypothesis (since now we know there is actually an effect)
-Our alternative hypothesis is supported so long as the relationship/correlation is in the appropriate direction