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MMW FINALS > HYPOTHESIS TESTING > Flashcards

HYPOTHESIS TESTING Flashcards

1
Q

What type of distribution is represented if the mean, median and mode have equal values?

A. Normal distribution
B. Negatively Skewed Distribution
C. Positively Skewed Distribution
D. Platykurtic Distribution

A

A. Normal distribution

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2
Q

Division of statistics that refers to the drawing of conclusions about the population based on a representative sample systematically taken from the same population.

A. Descriptive Statistics
B. Inferential Statistics
C. Business Statistics
D. Elementary Statistics

A

B. Inferential Statistics

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3
Q

This is a procedure, based on sample evidence and probability theory, used to determine whether the hypothesis is a reasonable statement and should not be rejected, or is unreasonable and should be rejected.

A

Hypothesis Testing

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4
Q

A statement that is accepted if the sample data provide evidence that null hypothesis is false.

A

ALTERNATIVE HYPOTHESIS

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5
Q

It refers to the statement that there is no difference between a parameter and a specific value.

A

NULL HYPOTHESIS

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6
Q

The mean content if the 500 bottles of soft drinks is found to be 965 ml. This is below the published content of 1 liter. What appropriate statistics will be used?

A

Z-TEST, because the sample is greater than 30

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7
Q

If the null hypothesis states that there is no association between the two variables and is not rejected, then it can be concluded that ___________________________________________

A. There is a significant relationship between the two variables between two variables.
B. The first variable is related to the first variable.
C. There is no significant relationship between the two variables.
D. The first variable is related to the second variable.

A

C. There is no significant relationship between the two variables.

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8
Q

The performance of the students in mathematics significantly improved after being exposed to the new strategy. What appropriate statistics will be used?

A. t-test for independent samples
B. t-test for dependent samples
C. ANOVA
d. z-test

A

B. t-test for dependent samples

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9
Q

If the t-stat (computed value ) is greater than the critical value, then we will

A. reject the null hypothesis
B. accept / fail to reject the null hypothesis
C. none of the above

A

A. reject the null hypothesis

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10
Q

If the t-stat (computed value ) is less than the critical value, then we will

A. reject the null hypothesis
B. accept / fail to reject the null hypothesis
C. none of the above

A

B. accept / fail to reject the null hypothesis

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11
Q

If we are going to test 2 or more groups, what statistical treatment should we use?

A. t-test for independent samples
B. t-test for dependent samples
C. ANOVA
d. z-test

A

C. ANOVA

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12
Q

If the sample are considered small or less than 30, then the statistical treatment to be used is

A. t-test
C. ANOVA
d. z-test

A

A. t-test

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13
Q

If there is one group of sample, and 2 observations (pretest and post-test) are tested, then the statistical treatment used is

A. t-test for independent samples
B. t-test for dependent samples / paired t-test
C. ANOVA
d. z-test

A

B. t-test for dependent samples/ paired t-test

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14
Q

If there are two groups to be tested, the statistical treatment would be

A. t-test for independent samples
B. t-test for dependent samples / paired t-test
C. ANOVA
d. z-test

A

A. t-test for independent samples

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15
Q

Given a set of data, if the mean is less than the median then,

A. the distribution is symmetric.
B. the distribution is positively skewed.
C. the distribution is negatively skewed.
D. it cannot be determined

A

C. the distribution is negatively skewed.

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16
Q

In a positively skewed distribution,

A. the mean is equal to the median.
B. the mean is greater than the median.
C. the mean is less than the median.

A

B. the mean is greater than the median.

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17
Q

TRUE OR FALSE: Only the values of central tendency is enough to describe the data.

A

FALSE, because the measures of variability is also important

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18
Q

It refers to the measures of the average distance of each observation from the center of the distribution

A

MEASURES OF VARIABILITY OR DISPERSION

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19
Q

measures the homogeneity and heterogeneity of a particular group

A

MEASURES OF VARIABILITY OR DISPERSION

20
Q

When the data have a small measure of variability, this indicates that the data are

  1. clustered closely around the mean
  2. more homogenous
  3. more consistent
  4. more uniformly distributed

A. 1 and 4 only
B. 1,2,3 only
C. 1 only
D. All of the above

A

D. All of the above

  1. clustered closely around the mean
  2. more homogenous
  3. more consistent
  4. more uniformly distributed
21
Q

Why do we not rely solely on the mean?

A

Because the mean only conclude the both groups performed equally well, but this does not explain how far apart the grades are from one another

22
Q

TRUE OR FALSE: The measure of the center helps describe and compare the data sets, considering the average distance of each item from the center of distribution.

23
Q

It is the difference between the highest and lowest values.

24
Q

Average of the squared deviation from the mean

25
Q

TRUE OR FALSE: The value of the variance determines if the mean is a good measure of central tendency.

26
Q

TRUE OR FALSE: A small variance indicates the observations are highly concentrated about the mean, thus it is appropriate to use the mean to represent all the values in the collection.

27
Q

TRUE OR FALSE: A large value of variance means that the observations are far or different from the mean, thus it is not a good measure of the central tendency.

28
Q

measure of the spread of scores within a set of data

A

STANDARD DEVIATION

29
Q

A descriptive measure of how the data entries differs from the mean

A

STANDARD DEVIATION

30
Q

It is computed by extracting the square root of the variance

A

STANDARD DEVIATION

31
Q

It states that the percentage of observed values that fall within the distances of K standard deviations below and above the mean must be at least (1-(1)/(K^2)) 100%
K > 1

A

BIENAYME AND CHEBYSHEV RULE

32
Q

p value is less than the alpha level, then

A

reject the null hypothesis

33
Q

are only used when the researcher wants to generalize about a population given a sample.

A

STATISTICAL TESTS

34
Q

When ASSUMPTIONS of the statistical tests are MET.
When sample size is considered LARGE
When data are NUMERICAL

A

PARAMETRIC

35
Q

When at least one ASSUMPTION of the statistical test is NOT MET.
When sample size is too SMALL.
When data are CATEGORICAL.

A

NON-PARAMETRIC

36
Q
  • DATA POINTS ARE INDEPENDENT
  • BASED ON NORMAL DISTRIBUTION
  • KNOWN POPULATION VARIANCE
  • LARGE SAMPLE SIZE
37
Q
  • DATA POINTS ARE INDEPENDENT
  • BASED ON STUDENT T-DISTRIBUTION
  • UNKNOWN POPULATION VARIANCE
  • SMALL SAMPLE SIZE
38
Q

CONTINUOUS
RANDOM SAMPLE
NORMALLY DISTRIBUTED

A

T-INDEPENDENT SAMPLES

39
Q

symbolized by H0, is a statistical hypothesis testing that assumes that the observation is due to a chance factor.

A

NULL HYPOTHESIS

40
Q

symbolized by H1 it states that there is a difference between two population means (or parameters)

A

ALTERNATIVE HYPOTHESIS

41
Q

refers to the degree of significance in which we accept or reject the null hypothesis.

A

LEVEL OF SIGNIFICANCE

42
Q

the maximum probability of committing a Type I error

A

LEVEL OF SIGNIFICANCE

43
Q

the range of the values of the test value that indicates that there is significant difference and that the null hypothesis (H0) should be rejected.

A

REJECTION OR CRITICAL VALUE

44
Q

is the range of the values of the test value that indicates that the difference was probably due to chance and that the null hypothesis (H0) should not be rejected.

A

NON-CRITICAL OR NON-REJECTION REGION

45
Q

shows that the H0 be rejected when test value is in the critical region on ONE SIDE OF THE MEAN

A

ONE-TAILED TEST

46
Q

he H0 should be rejected when the test value is in either of the two critical regions.

A

TWO- TAILED TEST

MMW FINALS (3 decks)

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