The distribution of the heights of the first grade students is mound – shaped and symmetric with the mean height of 140 cm and standard deviation of 5 cm.
According Empirical rule

What % of heights is between 125 and 155 cm

What % of heights is between 135 and 150 cm

What % of heights is less than 130 cm

What % of heights is less than 130 cm

To test the accuracy of the micrometer, the wire thickness was measured 60 times and an empirical standard deviation of 0.05 mm was obtained. Assuming that the distribution of measurement errors is normal, examine at the significance level 0.05 the hypothesis that the micrometer measures with an accuracy of 0.04 mm.
a) The test statistics with the relevant test is:
b) At the significance level of 0.05 WE REJECT / WE DO NOT REJECT H0

1. Determinants of FDI: there are about six key traditional determinants of FDI (firm-level and plant-level scale economies, trade costs, transportation costs, tax differentials, and cost of factors differentials) that are often used in empirical testing of FDI models. List and explain other factors (other than those listed above) that affect the location decisions of FDI/MNCs.

Empirical evidence shows that highly profitable firms tend to have lower debt ratios (debt to equity, debt to total capital, debt to assets, etc.). Briefly explain if this evidence supports or does not support the trade-off theory of capital structure. Also, briefly explain if this evidence supports or does not support the pecking order theory of capital structure.

​When a 1.50 g sample of aluminum metal is burned in an oxygen atmosphere, 2.83 g of aluminum oxide are produced. However, the combustion of 1.50 g ultrafine aluminum in air results in 2.70 g of a product, which is a mixture of 80% aluminum oxide and 20% aluminum nitride (% by mass). Use this information to determine the empirical formulas of aluminum oxide and luminum nitride.

Psychological Disorders.

Choose a disorder that the textbook covers that most interests you.

Discuss the definition of the disorder, symptoms, treatments, and why you chose this disorder.

Find a recent empirical article on your disorder (last 5 years). Briefly summarize the purpose, methods, and findings of your article.

How is this disorder typically portrayed in the media? Is it accurate based on your research?

Study Guide Chapter 3

What is average mass? What is average atomic mass? What is the atomic mass?

What is the mole? If you have a mole of cheese, how many pieces of cheese do you have?

What is the Avogdro’s number? What is this number used for?

How do we use the mole in chemical reactions?

Students must be able to calculate the mass of given numbers of atoms of an element. For example, calculate the mass of 10 atoms of carbon. See example 3.2.

Students must be able to calculate the moles of atoms. See example 3.3.

Students must be able to calculate number of atoms. See example 3.3.

Students must be able to calculate number of moles and mass.

What is molar mass? Students must be able to calculate the molar masses for a given compound. For example, calculate the molar mass of C₆H₁₂O₆. See examples 3.6 and 3.7 and 3.8.

Discuss, in as many details as you can, the conceptual problem solving approach.

What is percent composition? What is the percent mass composition of C₆H₁₂O₆. See example 3.9.

What is the formula of a compound? How can we determine the formula of a compound? How do we determine the empirical formula of a compound? What type of data do we need to have to determine the empirical formula for a compound? What type of data do we need to have to determine the molecular formula of a compound? How do we determine the molecular formula from the empirical formula?

A compound that contains only C, H and O is 48.64% C and 8.16% H. What is the empirical formula for this compound? See examples 3. 10 – 3.12.

What is a chemical reaction? What is a chemical equation? Describe a chemical equation in detail. Students must learn how to do read a chemical equation.

Why are we required to balance chemical equations? How do we balance chemical equations? See examples 3.13 – 3.14.

What is stoichiometric calculations? When do we perform such calculations? See examples 3.15 – 3.16.

What is a limiting reagent? How do we calculate the limiting reagent? What type of data do we need to calculate the limiting reagent?

What is theoretical yield? What is actual (experimental) yield? What is percent yield? What does percent yield mean?

Acme 3-D Printing Co. custom produces products for customers by using computerized 3D printing. An employee (clerk) at Acme takes orders from customers, each order contains the specifications for one “print job”: one custom 3D object to be manufactured. When the order is received, the employee immediately collects cash payment – no credit is extended to customers. The order takes about one week to put into production as a print job. The print job is a manufacturing process consisting of the application of different colored plastics which are shaped and milled into a single 3-dimensional object using various machine processes. Acme maintains information about its cash accounts, orders, print jobs, the employees (machinists) who perform each print job, customers, the quantities of different colored plastics used in each print job, and the processes that are performed on each print job. Each print job is manufactured by one employee who performs all the processes that are necessary for that print job. Print jobs manufactured for customers require one or more colored plastics, and one or more processes. Each customer could have many orders and many print jobs throughout the year; each print job requires a new order. All company data is currently contained in the following database:

CASH (ACCOUNT-NO, ACCT-TYPE, CASH-BALANCE)

ORDERS (ORDER-NO, ORDER-DATE, SPECS, ACCOUNT-NO*)

PRINT_JOB (JOB-NO, JOB-DATE, EMPLOYEE-NO, EMPLOYEE-NAME, MFG-TIME, CUSTOMER-NO, CUSTOMER-NAME, CUSTOMER-ADDRESS, PROCESS-NO*, ORDER-NO*)

COLORED_PLASTICS (JOB-NO*, CP-NO, CP-DESCRIPTION, QUANTITY-USED)

PROCESSES (PROCESS-NO, PROCESS-DESCRIPTION)

Definitions of some fields: Any -NO field is the unique identifier of a database entity SPECS is a text field that contains all the print job specifications taken during the order CP stands for “colored plastic” QUANTITY-USED field indicates the quantity of each colored plastic used on each print job. JOB-DATE is the date on which the print job is manufactured MFG-TIME is the amount of manufacturing time the entire print job takes

(1a.) Does this database contain a transitive dependency? If yes, describe ONE transitive dependency by naming the fields and how they create the dependency.

(1b.) Does this database contain a partial dependency? If yes, describe ONE partial dependency by naming the fields and how they create the dependency.

(1c.) Does this database contain a potential repeating group? If yes, describe ONE repeating group by naming a field that would repeat.

In Python: how can I fix the IsADirectoryError: [Errno 21] Is a directory: ???

this is my code:

#importing sqlite and pandas

import sqlite3

import pandas as pd

#goal

print("Welcome! The goal of this assigment is to create a database to find meanings and synonyms for given phrases.")

#Connecting database

conn = sqlite3.connect("keilavaldez.db")

#Creating cursor to remove existing specified tables

cur = conn.cursor()

#creating tables

cur.execute("CREATE TABLE Synsets([SynsetID] INTEGER,[Definition] text)")

cur.execute("CREATE TABLE Phrases([SynsetID] INTEGER,[phrase] text)")

conn.commit()

#opening and reading table named "synsets"

with open("//Users//keilavaldez//Desktop//assigment 10", 'r') as f:

for line in f:

data = line.split('\t')

cur.execute('INSERT INTO synsets (SynsetID, Definition) VALUES (?, ?)', (data[0], data[1].strip()))

#opening and reading table named "phrases"

with open("//Users//keilavaldez//Desktop//assigment 10", 'r') as f:

for line in f:

data = line.split('\t')

cur.execute('INSERT INTO phrases (SynsetID, phrase) VALUES (?, ?)', (data[0], data[1].strip()))

#Asking the user to enter a phrase

#checking if the phrase its in the database

#checking phrases even if they are lower

phrase = str(input("Please enter a phrase: "))

query = 'SELECT * FROM phrases WHERE phrase=' + "'"+ phrase.lower() + "'"

df = pd.read_sql_query(query, conn)

#if phrase is not in database, asking the user to try again

if df.empty:

print("Phrase/word not found. Please try again!")

#returning output if output is in database

#printing how many meanings the phrase has

#printing synonyms, printing unique synonyms

#prinit

else:

result_query = 'SELECT DISTINCT s.SynsetID,Definition FROM phrases p INNER JOIN synsets s ON s.SynsetID=p.SynsetID WHERE phrase=' + "'"+ word.lower() + "'"

result_df = pd.read_sql_query(result_query, conn)

lst = result_df['SynsetID'].values.tolist()

query = 'SELECT DISTINCT phrase,SynsetID FROM phrases WHERE SynsetID IN (SELECT DISTINCT s.SynsetID FROM phrases p INNER JOIN synsets s ON s.SynsetID=p.SynsetID WHERE phrase=' + "'"+ word.lower() + "') AND phrase<>"+ "'"+ word.lower() + "'"

df = pd.read_sql_query(query, conn)

syn = df['phrase'].values.tolist()

print("There are "+ str(len(lst)) +" meanings and "+ str(len(syn)) +" unique synonyms")

j=1

#priniting along with the synset ID

#printing all synonyms

for i in lst:

print("The meaning of this word: ",j)

print(result_df[result_df['SynsetID']==i]["The definition of this word: "].values[0])

print("Synset ID: ")

print(i)

print("Synonyms:")

words = df[df['SynsetID']==i]['phrase'].values.tolist()

for w in words:

if w!=phrase.lower():

print(w)

j=j+1