Which of the following actions most emerging economies took after facing with the prospects of global stagflation, nations, feeling compelled to protect their respective economic space?
I- Nation opted Protectionist Measures
II- Slowed down Cross border trade
III- Opened their economy more
The Covid-19 pandemic notified by the WHO in January 2020 was the first challenge of the third decade that hit global growth. Two years later, as the global economy was recovering from the pandemic-induced output contraction, the Russia-Ukraine conflict broke out in February 2022, triggering a swing in commodity prices and, thus, accelerating existing inflationary pressures. This posed the second challenge. Soon after, the third challenge emerged when nations undertook monetary tightening to rein in inflation causing growth to weaken. Monetary tightening also drove capital flows to safe-haven US markets, contributed to rising sovereign bond yields, and depreciation of most currencies against the US dollar. The consequent increase in borrowing costs also stressed high levels of public and private debt, threatening the financial system. Faced with the prospects of global stagflation, nations, feeling compelled to protect their respective economic space, slowed cross-border trade, which posed the fourth challenge to growth.
When identifying business problems, what is the first step a data analyst should take to ensure clarity and effectiveness in solving the problem?
In data transformation, what is the primary purpose of standardization?
In descriptive statistics, what is the main advantage of using the median over the mean as a measure of central tendency in data analysis?
Which method would be most effective in identifying the relationship strength between two continuous variables?
Which of the following is a key difference between random sampling and non-random sampling?
Which of the following is an example of an independent variable in a data analysis model that predicts employee productivity based on training hours?
During the data analysis process, which of the following steps is primarily focused on removing inaccuracies and ensuring the dataset's reliability?
Which of the following forecasting methods would be most suitable for a time series that exhibits both a long-term trend and seasonality?
Which of the following is not a measure of central tendency?
In data cleaning, which technique is most effective in handling outliers in a dataset that could skew analysis?
