F1.Any time there is a statistical association between events, we can assume there is causation.

T2.A binary variable is categorical data that can take only two values; for example: college grad = 1, not college grad = 0.

T3.Likert scales measure ordinal data with coding; the more scale points used, the coarser the scale.

T4.Characteristics of a population are called parameters; characteristics of a sample are called statistics.

T5.Of the seven sampling methods, only cluster sampling uses geographical areas as strata.

Problem section. Show all your work and uses only your own words (not words from the textbook)

A. Using the data below, create a scatter plot with EXCEL. Describe the relationship between the two variables (Unit Price and Units Sold) using the Figures on pp. 84-85. Unit Price: 5, 4, 6, 5.5, 6.25, 7

Units sold: 17, 16, 13, 17, 12, 10

B. What are the advantages and disadvantage of convenience sampling?

Advantages:
• It’s fast and quick
• It costs less because the samples can be used from anywhere that is accessible to the person conducting the research.

Disadvantages:
• Results are biased since there is a lack of representative people in the study. • Results may not be replicable when repeated

C. What is “skewness”? Will a right-skewed distribution have most of the values clustered on the right? Explain your answer!

In a histogram skewness is characterized by the direction of its longer tail, and if both tails are the same, it is considered symmetric. No, a right-skewed distribution has most of its values clustered on the left, hence why it is positively skewed. As our text book illustrates, right-skewed histograms are used by business data where it is often bounded by zero on the left but unbounded on the right.

D. What is a histogram and how do you decide how many bins...

...Design
Descriptive
Inferential
Population
Parameter
Sample
Random
Bias
Statistic
Types of
Variables
Graphs
Measurement scales
Nominal
Ordinal
Interval
Ratio
Qualitative
Quantitative
Independent
Dependent
Bar Graph
Histogram
Box plot
Scatterplot
Measures of
Center
Spread
Shape
Mean
Median
Mode
Range
Variance
Standard deviation
Skewness
Kurtosis
Tests of
Association
Inference
Correlation
Regression
Slope
y-intercept
Central Limit Theorem
Chi-Square
t-test
Independent samples
Correlated samples
Analysis-of-Variance
Glossary of Terms
Statistics - a set of concepts, rules, and procedures that help us to:
organize numerical information in the form of tables, graphs, and charts;
understand statistical techniques underlying decisions that affect our lives and well-being; and
make informed decisions.
Data - facts, observations, and information that come from investigations.
Measurement data sometimes called quantitative data -- the result of using some instrument to measure something (e.g., test score, weight);
Categorical data also referred to as frequency or qualitative data. Things are grouped according to some common property(ies) and the number of members of the group are recorded (e.g., males/females, vehicle type).
Variable - property of an object or event that can take on different values. For example, college major is a...

...Statistics Vocabulary
Chapter 1
Data are collections of observations ( such as measurements, genders, survey responses)
Statistics is the science of planning studies and experiments, obtaining data, and then organizing, summarizing, presenting, analyzing, interpreting, and drawing conclusion based on the data
A Population is the complete collection of individuals (scores, people, measurements and so on) to be studied. The collection is complete in the sense that includes ALL of the individuals to be studied
A census is the collection of data from EVERY member of the population
A sample is a subcollection of member selected from a population
A Parameter is a numerical measurement describing some characteristic of a population
A statistic is a numerical measurement describing some characteristic of a sample
Quantitative (or numerical) data consist of numbers representing counts or measurements
Categorical (or qualitative or attribute) data consist of names or labels that are not numbers representing counts or measurements
Discrete data result when the number of possible values is either a finite number or a “countable” number. (That is, the number of possible values is 0 or 1 or 2 and so on
Continuous (numerical) data result from infinitely many possible values that correspond to some continuous scale that covers a range of values without gaps, interruptions, or jumps
The nominal level of measurement is characterized by data...

...The History of statistics can be said to start around 1749 although, over time, there have been changes to the interpretation of the word statistics. In early times, the meaning was restricted to information about states. This was later extended to include all collections of information of all types, and later still it was extended to include the analysis and interpretation of such data. In modern terms, "statistics" means both sets of collected information, as in national accounts and temperature records, and analytical work which require statistical inference.
Statistical activities are often associated with models expressed using probabilities, and require probability theory for them to be put on a firm theoretical basis: see History of probability.
A number of statistical concepts have had an important impact on a wide range of sciences. These include the experiments and approaches to statistical inference such as Bayesian inference, each of which can be considered to have their own sequence in the development of the ideas underlying modern statistics.
The term statistics is ultimately derived from the New Latin statisticum collegium ("council of state") and the Italian word statista ("statesman" or "politician"). The German Statistik, first introduced by Gottfried Achenwall (1749), originally designated the analysis of data about the state, signifying the "science of state" (then called political...

...techniques.
Firstly we look at data analysis. This approach starts with data that are manipulated or processed
into information that is valuable to decision making. The processing and manipulation of raw
data into meaningful information are the heart of data analysis. Data analysis includes data
description, data inference, the search for relationships in data and dealing with uncertainty
which in turn includes measuring uncertainty and modelling uncertainty explicitly.
In addition to data analysis, other decision making techniques are discussed. These techniques
include decision analysis, project scheduling and network models.
Chapter 1 illustrates a number of ways to summarise the information in data sets, also known as
descriptive statistics. It includes graphical and tabular summaries, as well as summary measures
such as means, medians and standard deviations.
Uncertainty is a key aspect of most business problems. To deal with uncertainty, we need a basic
understanding of probability. Chapter 2 covers basic rules of probability and in Chapter 3 we
discuss the important concept of probability distributions in some generality.
In Chapter 4 we discuss statistical inference (estimation), where the basic problem is to estimate
one or more characteristics of a population. Since it is too expensive to obtain the population
information, we instead select a sample from the population and then use the information in the
sample to infer the...

...Trajico, Maria Liticia D.
BSEd III-A2
REFLECTION
The first thing that puffs in my mind when I heard the word STATISTIC is that it was a very hard subject because it is another branch of mathematics that will make my head or brain bleed of thinking of how I will handle it. I have learned that statistic is a branch of mathematics concerned with the study of information that is expressed in numbers, for example information about the number of times something happens. As I examined on what the statement says, the phrase “number of times something happens” really caught my attention because my subconscious says “here we go again the non-stop solving, analyzing of problems” and I was right. This course of basic statistic has provided me with the analytical skills to crunch numerical data and to make inference from it. At first I thought that I will be alright all along with this subject but it seems that just some part of it maybe it is because I don’t pay much of my attention to it but I have learned many things. I have learned my lesson.
During our every session in this subject before having our midterm examination I really had hard and bad times in coping up with this subject. When we have our very first quiz I thought that I would fail it but it did not happen but after that, my next quizzes I have taken I failed. I was always feeling down when in every quiz I failed because even though I don’t like this...

...of 1000 flights and proportions of three routes in the sample. He divides them into different sub-groups such as satisfaction, refreshments and departure time and then selects proportionally to highlight specific subgroup within the population. The reasons why Mr Kwok used this sampling method are that the cost per observation in the survey may be reduced and it also enables to increase the accuracy at a given cost.
TABLE 1: Data Summaries of Three Routes
Route 1
Route 2
Route 3
Normal(88.532,5.07943)
Normal(97.1033,5.04488)
Normal(107.15,5.15367)
Summary Statistics
Mean
88.532
Std Dev
5.0794269
Std Err Mean
0.2271589
Upper 95% Mean
88.978306
Lower 95% Mean
88.085694
N
500
Sum
44266
Summary Statistics
Mean
97.103333
Std Dev
5.0448811
Std Err Mean
0.2912663
Upper 95% Mean
97.676525
Lower 95% Mean
96.530142
N
300
Sum
29131
Summary Statistics
Mean
107.15
Std Dev
5.1536687
Std Err Mean
0.3644194
Upper 95% Mean
107.86862
Lower 95% Mean
106.43138
N
200
Sum
21430
From the table above, the total number of passengers for route 1 is 44,266, route 2 is 29,131 and route 3 is 21,430 and the total numbers of passengers for 3 routes are 94,827.
Although route 1 has the highest number of passengers and flights but it has the lowest means of passengers among the 3 routes. From...

...compliments the regular mathematics and therefore both are tested in primary schools. Mathematics is the written application of operation. It teaches students to think clearly, reason well and strategize effectively. Mental Mathematics is the ability to utilise mathematical skills to solve problems mentally. The marks scored by pupils generate statistics which are used by teachers to analyse a student’s performance and development of theories to explain the differences in performance.
The Standard 3 class is where the transition from junior to senior level occurs where teachers expect the transference of concrete to abstract thinking would have occurred.
A common theory by many primary school teachers is ‘Students perform better in Mathematics than Mental math. Mental math is something that has to be developed and involves critical thinking. Mental math requires quick thinking and the student must solve the problem in their minds whereas in regular mathematics, the problem can be solved visually. Therefore, teachers should take these factors into consideration while testing and marking students in these areas.’
In this study, the statistics of 30 students of a standard 3 class of San Fernando Boys’ Government School will be analysed to determine the truth of this theory.
DATA COLLECTION METHODS
Mathematics and mental mathematics marks of term 1 of the class of 2013 were obtained from a Standard 3 teacher of San Fernando Boys’...

...1. Exercises 1.57 & 1.58. Stock performance. Page 46
How well have stocks done over the past generation? The Standard & Poor’s 500 stock index describes the average performance of the stocks of 500 leading companies. Because each return is weighted by the total market value of each companys stock, the index emphasizes larger companies. The file ex01 57.txt contains the real (that is, adjusted for the changing buying power of the dollar) returns on the S&P 500 for the years from 1971 to 2003.
(a) Make a histogram of the real returns. Describe the shape of the distribution.
Answer) The Histogram for the real Returns, of Standard and Poor’s stock Index can be plotted using the following “R” commands:
>table table
Please refer to the following screenshot:
Once the above command is executed, we can attach the table “table” using the following attach command:
>attach (table)
Please Refer to the following screenshot:
1. Exercises 1.57 & 1.58. Stock performance. Page 46
How well have stocks done over the past generation? The Standard & Poor’s 500 stock index describes the average performance of the stocks of 500 leading companies. Because each return is weighted by the total market value of each companys stock, the index emphasizes larger companies. The file ex01 57.txt contains the real (that is, adjusted for the changing buying power of the dollar) returns on the S&P 500 for the years from 1971 to 2003.
(a) Make a histogram of the real returns. Describe the...