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Business Research > Quantitative Data Analysis > Flashcards

Quantitative Data Analysis Flashcards

1
Q

What is a null hypothesis?

A
  • The null hypothesis is the base line
  • In experimental research the null hypothesis is that nothing will change
  • We accept or reject the null hypothesis
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2
Q

What is an experimental hypothesis?

A
  • The experimental hypothesis is what we predict
  • We can have more than 1 experimental hypothesis
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3
Q

What is a Type I Error?

A

When we reject a null hypothesis that is true.

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4
Q

What is a Type II Error?

A

When we do not reject a false null hypothesis (we accept a null hypothesis that is false).

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5
Q

What are the 4 stages in the process of hypothesis testing?

A
  1. Hypothesis formulation
  2. Specification of significance level
  3. Selection of appropriate statistical test
  4. Calculation of the test statistic and acceptance or rejection of the hypothesis
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6
Q

Types of hypothesis

A
  • hypothesis about a single population
  • hypothesis about comparisons between two groups
  • hypothesis about the relationship between variables
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7
Q

What is the significance level?

A
  • The significance level measures the probability of making a mistake
  • The significance level has to be decided on the basis of the expected consequences of a type I error and a type II error, before the test is conducted
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8
Q

What is the significance level if we believe a type I error is more severe?

A

0.01 or 0.001

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9
Q

What is the significance level if we believe a type II error is more severe?

A

0.1

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10
Q

What is the significance level if we believe a type I error and a type II error are equally severe?

A

0.05

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11
Q

Selection of appropriate statistical test

A

The selection of the test depends on the type of data we have collected

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12
Q

What are the types of data?

A

Categorical and Quantifiable

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13
Q

What are the types of categorical data?

A

Nominal and Ordinal

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14
Q

What are the types of quantifiable data?

A

Interval and Ratio

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15
Q

What is Nominal data?

A

Nominal data constitute a name value or category with no order or ranking implied

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16
Q

What is Ordinal data?

A

Ordinal data comprises an ordering or ranking of values, although the intervals between the ranks are not intended to be equal

17
Q

When do we use Ordinal data?

A

Ordinal scales are used for questions that rate the quality of something and agreements

18
Q

What is Interval data?

A

Numerical values are assigned along an interval scale with equal intervals, but there is no zero point where the trait being measured does not exist.

19
Q

What is Ratio data?

A

Ratio data are a subset of interval data, and the scale is again interval, but there is an absolute zero that represents some meaning.

20
Q

When do we use a One-sample t-test?

A

When we have one variable of interest and that variable is quantifiable.

21
Q

What test do we use when the independent variable is nominal and the dependent variable is quantifiable?

A

Dependent t-test or Independent t-test

22
Q

When do we use Regression analysis?

A

When we have two variables of interest and they are both quantifiable.

23
Q

What is the One-sample t-test

A

A statistical test based on the mean and the standard deviation of the data when the variable of interest is quantifiable

24
Q

How do we determine if we reject H0?

A

To determine if we should reject H0 or not, we compare the probability of making a type 1 error in this test (the p-value or Sig. in SPSS) with the significance level we set.
If p-value < sig.level: reject H0.
If p-value > sig.level: do not reject H0.

25
Q

How do we write a conclusion?

A

We always refer to the t statistic and the p value.
Example:
Conclusion:
We reject H0. There is enough evidence to infer that the new machine packs faster than the old machine (t = -6.416, p-value = 0.000).

26
Q

What are the Dependent t-Test and Independent t-Test?

A

Both tests compare the average value of a dependent variable between two groups (independent variable).

27
Q

When do we use the Independent t-Test?

A

When we compare the average value of the dependent variable between two independent groups.
Example: People who have received the IELTS training vs people who have not

28
Q

When do we use the Dependent t-Test?

A

When we compare the average value of the dependent variable for one group, twice.
Example: English proficiency before and after the IELTS training

29
Q

What is the advantage of the Dependent t-test over the Independent t-test?

A

The advantage of the dependent t-test is that it controls for extraneous variables.

30
Q

What is Regression analysis?

A

In regression analysis we test if there is a linear relationship between the independent and dependent variable and if this relationship is positive or negative.
- We want to come up with a model to predict the relationship

Business Research (6 decks)

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