Answer:
The correct answer is C. C)"I know these cigarettes are killing me but I just can't stop."
Explanation:
Luis picks up a pack of cigarettes and reads,"Cigarette smoking is harmful to your health." The statement that leads one to believe Luis is actually having cognitive dissonance is " I KNOW THESE CIGARETTES ARE KILLING ME BUT I JUST CAN'T STOP."
Answer:
DescriptionAbolitionism, or the abolitionist movement, was the movement to end slavery. This term can be used both formally and informally. In Western Europe and the Americas, abolitionism was a historic movement that sought to end the Atlantic slave trade and set slaves free.
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Answer:
The Kingdom of Israel was destroyed around 720 BCE, when it was conquered by the Neo-Assyrian Empire. While the Kingdom of Judah remained intact during this time, it became a client state of first the Neo-Assyrian Empire and then the Neo-Babylonian Empire.
Explanation:
Driving and smoking are risks that are not currently well-understood.-----
false
Smoking:
Smoking is addictive, which means that once a person has smoked regularly for some time, his or her body will crave more smoking, especially when the body's level of nicotine begins to drop because nicotine is leaving the body and no new dose has been ingested to replace it. Smokers probably cannot stop themselves from having these desires, but they may still be able to refrain from acting on them.
Driving :
Driving while you are distracted (e.g., while you are texting or using your cell phone). Driving when you are fatigued. Driving too fast when the roads are slippery or when weather is bad, such as in fog, rain, snow. Ignoring traffic laws, such as speeding, passing a stop sign/light, passing illegally, etc.
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.The simple split partitions the data into two mutually exclusive subsets called a training set and a test set . It is common to designate two-thirds of the data as the training set and the remaining one-third as the test set.
How do you measure accuracy of classification models?
There are many ways for measuring classification performance. Accuracy, confusion matrix, log-loss, and AUC-ROC are some of the most popular metrics. Precision-recall is a widely used metrics for classification problems
Classification accuracy:
is a metric that summarizes the performance of a classification model as the number of correct predictions divided by the total number of predictions. It is easy to calculate and intuitive to understand, making it the most common metric used for evaluating classifier models.
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