Les 4 - DATA PROCESSING AND STATISTICAL TREATMENT Flashcards

1
Q

involves the conversion of data in either manually or digitally into quantitative and qualitative forms for use in research analysis. It involves 3 general steps.

A

Data Processing
1. Categorization
2. Coding
3. Tabulation of Data

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Nature of statistics

A

A. As a body of knowledge or science (study of data, population/s, variations, distributions)
B. As a mass of data

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Two Major Areas of Statistics

A

Descriptive and Inferential Statistics

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

concerned with the methods for collection, organizing, and describing a set of data so as to yield meaningful information.

A

Descriptive Statistics

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

comprises those procedures for drawing inferences or making generalizations about characteristics of a population based on partial and incomplete information obtained from a sample of the population

A

Inferential Statistics

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Parameter vs Statistic (differences in meaning and symbols used)

A

A parameter is a number describing a whole population (e.g., µ, σ), while a statistic is a number describing a sample (e.g., x̄, sd)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

is any trait or attribute that vary from
person to person or case to case

A

variable

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

_______________ refer to any recorded information derived from counts, measurements, observations, interviews, experiments and other techniques. The data originally measured are referred to as _______________.

A

Statistical Data; Raw Data

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

Qualitative vs Quantitative Variables

A

classifies objects or cases according to the type or quality (qualitative) or the degree or amount (quantitative) of their attributes

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

Discrete vs Continuous Variables

A
  1. Discrete variable – the observations on the
    variable are countable units, expressed as
    whole numbers
  2. Continuous variable – can assume an
    infinitely large number of small, fractional
    values on a continuum
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

classifies data into distinct categories in which no ranking is implied. Weakest form of measurement.

A

Nominal

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

classifies values into distinct categories in which ranking is implied.

A

Ordinal

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

is an ordered scale in which the difference between measurements is a meaningful quantity but does not involve a true zero point; difference has the same meaning anywhere on the scale.

A

Interval

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

is an ordered scale in which the difference between the measurements involves a true zero point, as in height, weight, age, or salary measurements

A

Ratio

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

Identify the the levels of measurement of the following: Exam score, temperature in C, Age, Types of Rocks, Officer Hierarchy, Cost of Unliwings

A

Exam score, temperature in C, Age, Types of Rocks, Officer Hierarchy, Cost of Unliwings

Interval, Interval, Ratio, Nominal, Ordinal, Ratio

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

is a powerful statistical software platform that offers a user-friendly interface and a robust set of features that lets your organization quickly extract actionable insights
from your data according to International Business Machines Corporation (IBM)

A

SPSS (Statistical Package
for Social Sciences)

17
Q

SPSS Statistical Steps

A

Setting up a Data File, Preparing a Code Book, Putting your ideas into work, Creating on SPSS Data File, Hypothesis Testing: P-value Approach

18
Q

If null hypothesis is true but rejected.

A

Type I Error

19
Q

If null hypothesis is wrong but failed to reject

A

Type II Error

20
Q

Type of Error: Saying you’re pregnant to a man

A

Type I Error

21
Q

Type of Error: Saying you’re not pregnant to a pregnant woman

A

Type II Error

22
Q

concerned with the brief descriptive coefficients that summarize a given data set, which can be either a representation of the entire population or a sample of a population. Includes measures of central tendency and measures of variability (spread).

A

Descriptive Statistics

23
Q

It is better to use __________ on categorical variables and ____________ for continuous variables in Descriptive Statistics.

A

Frequencies, Descriptives

24
Q

Normality Value for Skewness, Kurtosis, Z-score, COV, Shapiro-Wilk’s W test, and Kolmogorov-Smirnov test?

A

Normality Value for Skewness, Kurtosis, Z-score, COV, Shapiro-Wilk’s W test, and Kolmogorov-Smirnov test?
± 2, ± 7, ± 3, <30%, >α (one-tailed) or >α/2 (two-tailed), >α (one-tailed) or >α/2 (two-tailed)

25
Q

It is useful for identifying outliers

A

Z-score

26
Q

One-tailed or Two-tailed?
A.
Ho: µ = 100
Ha: µ ≠ 100
B.
Ho: µ = 100
Ha: µ > 100

A

A. Two-tailed
B. One-tailed

27
Q

is a measure of association between
two variables. The variables are not designated as dependent or independent

A

Correlation

28
Q

Pearson correlation for 2 samples (r), Interpret results:
α = 0.01
r = -0.774
Sig. (2-tailed) = 0.003

A

The correlation is SIGNIFICANT (Sig. < α) the relationship is NEGATIVE and the degree and strength of association between two scores is VERY GOOD (0.774 or 77.4% is within 0.66-0.85)