Data presentation and interpretation Flashcards

(27 cards)

1
Q

what is discrete data ?

A

data that needs to be counted

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2
Q

What is the purpose of a frequency table for grouped data ?

A

It is used for large amounts of continuous data to show the frequency of data values within particular groups or classes.

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3
Q

How can you clarify grouping for discrete data ?

A

Use groups like 10–19 and 20–29 to avoid overlap

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4
Q

How should continuous data be grouped to avoid ambiguity ?

A

Use inequalities like
10 ≤ 𝑥 < 20 10 ≤ x < 20 and 20 ≤ 𝑥 < 30 20 ≤ x <30.

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5
Q

How should you adjust boundaries if there are gaps in continuous data ?

A

Modify the boundaries to avoid gaps, such as changing
10 ≤ x ≤ 19 and 20 ≤ x ≤ 29 to
9.5 ≤ x < 19.5 and 19.5 ≤ 𝑥 < 29.5

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6
Q

How do you find the modal class in a grouped frequency table ?

A

The modal class is the class with the greatest frequency.

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7
Q

What can you estimate from a grouped frequency table ?

A

You can estimate the mean and median, but not the exact values.

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8
Q

How do you estimate the mean from a grouped frequency table ?

A
  1. Find the midpoint of each class.
  2. Multiply each midpoint by its corresponding frequency.
  3. Find the sum of these values and divide by
    𝑛 (the total frequency).
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9
Q

What is variance ?

A

Variance measures how spread out or varied a set of data is from the mean.

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10
Q

What does a high variance indicate ?

A

A high variance means the data is more spread out from the mean.

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11
Q

How is standard deviation related to variance ?

A

The standard deviation is the square root of the variance.

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12
Q

What is the symbol for population standard deviation and variance ?

A

Standard deviation: σ , Variance: σ²

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13
Q

What are the main features of a cumulative frequency graph ?

A

Cumulative frequency is plotted on the y-axis.

The x-axis typically shows the upper boundaries of the classes.

The graph accumulates frequencies from each class, including those below it.

Data points are connected with a smooth curve (or straight lines).

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14
Q

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

A

A histogram displays grouped continuous data, whereas a bar chart is for discrete or qualitative data.

In a histogram, there are no gaps between bars, unlike in bar charts.

The height of the bar represents frequency density (not frequency).

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15
Q

What are the key features of a histogram ?

A

No gaps between bars (unless there are missing data).

Class widths may vary.

Frequency density is plotted on the y-axis.

Area of each bar represents the frequency for that class.

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16
Q

How do you calculate frequency density ?

A

FrequencyDensity=
ClassWidth / Frequency

17
Q

How are outliers calculated using the interquartile range (IQR) ?

A

A value is an outlier if it is:

Less than 𝑄1 − 1.5 x IQR

Greater than 𝑄3 + 1.5 x IQR

18
Q

How are outliers calculated using standard deviation ?

A

Less than
𝑥ˉ - 2𝜎

Greater than
𝑥ˉ + 2𝜎

19
Q

What is linear regression ?

A

Linear regression is used when there is a strong linear correlation in a scatter diagram. A line of best fit is drawn to approximate the relationship between two variables, representing a linear relationship.

20
Q

What is the Product Moment Correlation Coefficient (PMCC) ?

A

The PMCC is a numerical measure of the linear correlation between two variables in bivariate data. It is denoted by r.

21
Q

What range can the PMCC (r) take ?

A

−1 ≤ r ≤ 1

22
Q

Why do we use hypothesis testing for correlation ?

A

Hypothesis testing is used to determine if the product moment correlation coefficient (PMCC) from a sample is representative of the relationship in the entire population. It’s often impractical to collect data from the whole population.

23
Q

What is the PMCC for the whole population and the sample ?

A

The PMCC for the whole population is denoted by ρ, and the PMCC for a sample is denoted by r.

24
Q

What is the null hypothesis (H₀) for a correlation test ?

A

The null hypothesis is always: H₀: ρ = 0

25
What is the alternative hypothesis (H₁) in a hypothesis test for correlation ?
For a one-tailed test: H₁: ρ > 0 (+ correlation) or H₁: ρ < 0 (- correlation). For a two-tailed test: H₁: ρ ≠ 0 (there is a correlation).
26
How do you conduct a hypothesis test using critical values?
Compare r with the critical value from a table. If |r| > critical value, reject the null hypothesis If |r| ≤ critical value, not enough evidence to reject the null hypothesis
27
How do you conduct a hypothesis test using a p-value?
If the p-value is less than the significance level, reject the null hypothesis. If the p-value is greater than the significance level, accept the null hypothesis.