Keisha surveyed a group of people to find their age and their shoe size. She then graphed the order pairs (age, show size) For each person. Which one of the scatter plots most likely represents her graph
As an AI language model, I don't have the visuals to determine the correct scatter plot, but typically, age and shoe size are not highly correlated variables. Therefore, the scatter plot is likely to show a random pattern with points scattered throughout the graph without any clear pattern or trend line. It is also possible that there may be outlier points.
Fernando surveyed a group of people to find their shoe size and the number of children in their family. He graphed ordered pairs (Shoe size, number of children) for each person. Which of the scatter plots most likely represents his graoh? negative trend
no trend or positive trend
As an AI language model, I don't have the visuals to determine the exact scatter plot, but it is less likely that there is a clear negative trend between shoe size and the number of children in a family. However, it is also not easy to predict the scatter plot's direction without having more information about the data and the context of the survey. If Fernando's hypothesis is that having more children in a family makes parents wear smaller shoe size, it could show a negative trend. On the other hand, if there is no relationship or a positive relationship between shoe size and the number of children, the data would not show a clear negative trend.
so positive trend?
It is not possible to determine whether Fernando's scatter plot would show a positive trend without further information about the data and the context of the survey. If the hypothesis is that parents with larger feet tend to have more children in the family, then there could be a positive trend. But if there is no relationship or a negative relationship between shoe size and the number of children, then there would not be a positive trend.
the graph below shows the number of new clients brought into sunnydays insurance comapny. Why is the graph misleading?
As an AI language model, I do not have access to the graph you are referring to. However, graphs can be misleading for several reasons. Here are a few possibilities:
1. Incomplete or incorrect data: The graph may be misleading if it represents incomplete or incorrect data. For example, if some data is missing or if the data was not collected in a representative or unbiased way, the graph may not accurately reflect what it claims to represent.
2. Scale of the y-axis: The scale of the y-axis can also mislead viewers. If the scale is not proportional or if it starts at a number other than 0, it can make the data look more or less significant than it actually is. For example, if the y-axis starts at a value greater than 0, it can make the difference between the bars seem bigger than it actually is.
3. Misleading labels or titles: Sometimes the graph's labels or titles may be misleading, by not conveying what the graph is representing correctly.
4. Misleading graphics or colors: Sometimes, the graphics or the colors used in the graph can be misleading because it can exaggerate differences or make patterns seem more significant than they are.
To determine why the particular graph you are referring to is misleading, I will need more information about the graph.