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Pre-Course Assessment Quiz
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1. What is the primary goal of data analysis?
Making predictions
Summarizing and interpreting data
Designing databases
Data visualization
2. Which of the following is not a step in the Data Analysis process:
Define the problem or research question
Clean the data
Analyze the data
Meet with project stakeholders
3. What is the difference between mean and median?
Mean is the middle value; median is the average.
Mean is the average; median is the middle value.
Both represent the average.
Mean and median are used interchangeably.
4. What does the term "outlier" mean in data analysis?
The most common value in a dataset
Unusual or extreme values in a dataset
The difference between mean and median
The last value in a sorted dataset
5. How is the range of a dataset calculated?
The difference between the largest and smallest values
The sum of all values
The product of all values
The average of all values
6. What does a histogram visualize?
Relationships between two variables
Distribution of a single variable
Hierarchical data structures
Time-series data
7. What is the purpose of correlation in data analysis?
Causation between variables
Describing the spread of data
Measuring the strength and direction of a linear
Identifying outliers
8. What is the significance of the term "standard deviation"?
Measuring central tendency
Describing the spread or dispersion of data
Identifying the most frequent value
Representing the range of values
9. What is the purpose of a box plot in data analysis?
Representing the distribution of a single variable
Showing the relationship between two variables
Identifying outliers and displaying the spread of data
Displaying hierarchical relationships
10. What is a correct syntax to output the phrase "Hello World" in Python?
print(“Hello World”)
echo “Hello World”
p(“Hello World”)
echo(“Hello World”)
Next
11. Which is a correct way to insert a comment in python code?
//This is a comment
#This is a comment
/*This is a comment*/
— This is a comment
12. Which one of these would NOT be a valid variable name in Python?
Myvar
_myvar
my_var
my-var
13. How do you create a variable with the numeric value 5?
x = 5
x = int(5)
x = number 5
Options a and b
14. How do you create a variable with the floating number 2.8?
x = 2.8
x = float 2.8
x = float(2.8)
Options a and c
15. What is the correct syntax to output the type of a variable or object in Python?
typeof(x)
type(x)
typeOf(x)
typeof x
16. What is the correct way to create a function in Python?
create myFunction():
def myFunction():
function myfunction():
func myFunction():
17. In Python, 'Hello', is the same as "Hello"
True
False
18. Which method can be used to remove any whitespace from both the beginning and the end of a string?
trim()
ptrim()
len()
strip()
19. Given a variable name my_var with value “Hello”. Which of the following will output the first character ‘H’ in the word “Hello”.
my_var.first()
my_var[0]
my_var[1]
my_var 1
20. Which operator is used to multiply numbers?
*
%
x
#
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21. Which operator can be used to compare two values?
#>
==
><
=
22. Which of these collections is a python LIST?
[“apple”, “banana”, “cherry”]
{“apple”, “banana”, “cherry”}
{“name” : “apple”, “color” : “green”}
(“apple”, “banana”, “cherry”)
23. If variable x is 5 and variable y is 10, what would be the result of this expression in python? x < y
5
True
10
False
24. If variable x is 7 and variable y is 14, what would be the result of this expression in python? x / y
2
0.5
True
False
25. What is a correct syntax to create a Pandas DataFrame?
pd.DataFrame(data)
pd.dataframe(data)
pd.df(data)
pd.data
26. Which of these will remove duplicate rows from a dataset?
df.remove_rows()
df.drop_duplicate()
df.drop_duplicate_rows()
df.remove_duplicate()
27. Which of these will output the count of distinct values in a column?
unique()
nunique()
distinct()
values_count()
28. Which of the following will return a descriptive statistics of your dataset?
df.subscribe()
df.summary()
df.describe()
df.stats
29. Which of the following will detect missing values in data?
pd.missing()
pd.isnull()
pd.is_missing()
pd.null()
30. Which of the following will fill missing values in data?
df.fill_missing()
df.fillna()
df.fill_rows()
df.fill_columns()
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