2024-04-19 Kenyan Shilling News
2024-04-18
Summary of Yesterday
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
Understanding the overall trend of the exchange rates
The dataset provided consists of constant timestamp intervals, and exchange rates ranging mostly between 0.01034 and 0.01044. An initial glance at the data does not reveal an obvious overall trend towards an increase or decrease in exchange rates. The rates appear to oscillate within this narrow range, showing minor fluctuations rather than a clear upward or downward movement. To accurately quantify the overall trend, a trend analysis which includes a regression model or moving average technique could be used. However, based on the raw data alone, it would be safe to say that the exchange rates remained relatively stable over the period shown.
Identifying any seasonality or recurring patterns
Given the short interval of timestamp data provided, identification of seasonality or recurring patterns is a challenge. A dataset spanning a larger time frame would potentially allow for more accurate identification of such patterns but it's not visible in the current set. Although, it appears there is no obvious regular pattern or seasonality judging by the provided data. The exchange rates show minor fluctuations within the specified range, but these do not appear to be tied to a specific time or recurring event.
Outliers in the dataset
The range of the exchange rates in the dataset is very narrow (from 0.01034 to 0.01044), so any rate falling outside this interval might be considered as an outlier. However, Despite it being relevant to point out the exchange rate peak at 0.01044, it's important to consider the real-world significance of such a variation due to small variation. Given the stable nature of the data, a rate significantly higher or lower than the observed range would be an interesting point for potential future analysis with more varied data.