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GR 11 > STATS END TERM EXAM > Flashcards

STATS END TERM EXAM Flashcards

1
Q

is selected from the population and the data gathered from it will represent the data that can be gathered from the entire population.

A

sample

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2
Q

is concerned with the selection of a subset of population that will be used to estimate the characteristics of the entire population.

A

Sampling technique

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3
Q

is a statistical error that occurs when an analyst does not select a sample that represents the entire population of data. As a result, the results found in the sample do not represent the results that would be obtained from the entire population

A

Sampling Errors

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4
Q

TYPES OF SAMPLING ERRORS

A

Population-Specific Error
Selection Error
Sample Frame Error
Non-response Error

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5
Q

occurs when a researcher understands who to survey.

A

Population-Specific Error

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6
Q

occurs when the survey is self directed, or when only those participants who are interested in the survey respond to the questions. Researchers can attempt to overcome selection error by finding ways to encourage participation.

A

Selection Error

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7
Q

occurs when a sample is selected from the wrong population data

A

Sample Frame Error

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8
Q

occurs when a useful response is not obtained from the surveys because researchers were unable to contact potential respondents (or potential respondents refused to respond).

A

Non-response Error

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9
Q

SLOVIN’s FORMULA

A

𝑛 = 𝑁 / 1 + 𝑁𝑒 2

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10
Q

TYPES OF SAMPLING TECHNIQUES

A

Probability Sampling
Non-Probability Sampling

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11
Q

it is a sampling procedure where every element of a population is given an equal chance of being selected as a member of a sample.

A

Probability Sampling

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12
Q

This is a sampling procedure in which an element of the population is not given an equal chance of selected sample.

A

Non-Probability Sampling

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13
Q

TYPES OF PROBABILITY SAMPLING

A

Simple Random Sampling
Systematic Sampling
Stratified Sampling
Cluster Sampling

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14
Q
  • This is the most basic sampling technique
  • It is a sampling technique in which every element of the population has the same probability of being selected for inclusion in the sample.
A

Simple Random Sampling

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15
Q
  • Is another type of probability sampling which is also known as interval sampling.
A

Systematic Sampling

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16
Q
  • This method considers an interval in selecting a sample from a given population.
A

Systematic Sampling

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17
Q
  • Is a random sampling technique in which a list of elements of the population is used as a sampling frame and the elements to be included in the desired sample are selected by skipping through the list at regular intervals.
A

Systematic Sampling

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18
Q
  • Is a random sampling method that divides a population into different homogeneous subgroups called strata. Random samples will be selected from each stratum so that the population will be well presented. We use stratified random sampling when we consider subgroups like year level of students, gender and age, among others.
A

Stratified Sampling

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19
Q
  • Is a random sampling technique in which the population is first divided into strata and then the samples are randomly selected separately from stratum.
A

Stratified Sampling

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20
Q

is the subset of strata.

A

Stratum

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21
Q

This type of random sampling is also called area sampling because it is usually used on a geographical basis.

A

Cluster Sampling

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22
Q

requires a complete list of clusters that represent the sampling frame. Choose a few clusters randomly as a source of primary data and the data that can be collected from each cluster to represent the characteristics of the whole population.

A

Cluster Sampling

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23
Q

TYPES OF NON-PROBABILITY SAMPLING

A

Convenience Sampling
Purposive Sampling
Quota Sampling
Snowball Sampling

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24
Q
  • Selecting a participant because they are often readily and easily available.
  • Tends to be a favored sampling technique among students as it is inexpensive and an easy option compared to other sampling techniques.
  • This often helps to overcome many of the limitations associated with research.
  • Also known as accidental, opportunity or grab sampling.
A

Convenience Sampling

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25
Q

or judgmental sampling is a strategy in which particular settings, persons, or events are selected deliberately in order to provide information that cannot be obtained from other choices.

A

Purposive Sampling

26
Q

Samples are chosen based on the goals of study. They may be chosen based on their knowledge of their being conducted or if they satisfy the traits and conditions set by the researcher.

A

Purposive Sampling

27
Q

It requires careful planning and justification to ensure your sample is representative of the population you’re interested in studying.

A

Purposive Sampling

28
Q

participants are chosen on the basis of predetermined characteristics so that the total sample will have the same distribution of characteristics as the wider population

A

Quota Sampling

29
Q

If the desired quota is reached, the drawing of samples is terminated.

A

Quota Sampling

30
Q

uses a few cases to help encourage other cases to take part in the study, thereby increasing sample size.

A

Snowball Sampling

31
Q

This approach is most applicable in small populations that are difficult for access due to their closed nature (like secret and inaccessible professions).

A

Snowball Sampling

32
Q

Participants in the study were asked to recruit other members for the study.

A

Snowball Sampling

33
Q

is a number describing a whole population.

A

parameter

34
Q

is a number describing a sample.

A

statistic

35
Q

is an area of statistical inference wherein we can evaluate a conjecture about some of the characteristics of a population based on the data gathered from the sample.

A

Hypothesis testing

36
Q

is an educated guess that can be tested.

A

Hypothesis

37
Q

This type of error rejects the null hypothesis when in fact it is true.- error is also known as alpha (𝛼) error.

A

Type I Error

38
Q

This type of error fails to reject the null hypothesis when in fact it is false. - is also known as beta (𝛽) error.

A

Type II Error

39
Q

depends on the statistician or researcher who is willing to commit type I error.

A

level of significance

40
Q

is used when the alternative hypothesis is directional. It means that the value of the measures is either greater than or less than the other measure.

A

one-tailed test

40
Q

is a hypothesis where the rejection region lies at only one tail of the distribution.

A

one-tailed test

41
Q

is used when the alternative hypothesis is non-directional, which means that the values of two

A

two-tailed test

42
Q
  • is a hypothesis test where the rejection region lies on both end tails of the distribution, one on the left and one on the right.
A

two-tailed test

43
Q

This is used as a basis for deciding whether the null hypothesis should be subjected.

A

Test statistics

44
Q

This is the set of values of the test statistic that leads to rejection of null hypothesis.

A

Rejection region

45
Q

This is the set of values of the test statistic that leads to acceptance of the null hypothesis.

A

Non-rejection region

46
Q

This is the set of values of the test statistic that separates the rejection and non-rejections

A

Critical Value

47
Q

is a procedure in making decisions based on sample evidence or probability theory used to determine whether the null hypothesis is accepted or rejected. If the statement is found reasonable, then the hypothesis will be accepted, otherwise it will be rejected.

A

Hypothesis testing

48
Q

is the variable that may affect the dependent variable to change.

A

Independent variable

49
Q

is the variable that is influenced or affected by the independent variable.

A

Dependent variable

50
Q

The data collected in this type of study involves two variables called

A

bivariate data.

51
Q

are diagrams that used to show the degree and pattern of relationship between two sets of data. They are constructed on the xy coordinate plane. Each data point on a scatter plot represents two values (x,y).

A

Scatter Plots

52
Q

The of the point is the value of the independent variable (x)

A

abscissa

53
Q

the is the value of the dependent variable (y).

A

ordinate

54
Q

If the dots are on a straight line pointing upward to the right.

A

Perfect positive correlation

55
Q

If the dots are on the straight line pointing downward to the right

A

Perfect negative correlation

56
Q

If the dots are concentrated around a straight line pointing upward to the right.

A

Strong positive correlation

57
Q

If the dots are concentrated around the straight line pointing downward to the right.

A

Strong negative correlation

58
Q

If the dots are not close but are not too far from the straight line that they seem to follow

A

Moderately positive or negative correlation

59
Q

If the dots in the scatter plot are widely spread.

A

Weak positive or negative correlation

60
Q

If the dots are neither following a straight line pointing upward or downward to right nor have a pattern.

A

NO CORRELATION

61
Q

denoted by r measures the strength of the linear relationship. To find r, the following formula is used.

A

Pearson Product Moment Correlation Coefficient

GR 11 (19 decks)

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